The 500 largest companies in the USA Data Analysis¶
In [24]:
# import libraries
import requests # open web connection
import time
import datetime
# Connect to Website and pull in data
URL = 'https://www.50pros.com/fortune500'
# URL = 'http://localhost:9088'
# Set the headers for the Web Browser.
# You can get it from 'https://httpbin.org/get' and take a look at 'User-Agent' element.
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36", "Accept-Encoding":"gzip, deflate", "Accept":"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", "DNT":"1","Connection":"close", "Upgrade-Insecure-Requests":"1"}
# Open web connection to the website
page = requests.get(URL, headers=headers)
print(page)
<Response [200]>
In [ ]:
# Scrap the Web content for table
import pandas as pd
pd.set_option('display.max_rows', None)
df = pd.read_html(URL)
df[0]
In [25]:
# Save the scraped content into CSV file
# df.to_csv(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\The_500_Largest_Companies_in_USA\Largest_500_Companies.csv', index = False)
In [1]:
##### Read 500 Largest Companies from stored CSV file
# Import all needed modules
import pandas as pd
import geopandas as gpd # pip install geopandas if it's not installed yet
import matplotlib.pyplot as plt
import mapclassify # pip install mapclassify if not yet installed
import folium
# Set to display all columns
pd.set_option('display.max_columns',None)
pd.set_option('display.max_rows',None)
pd.options.display.float_format = '{:,.0f}'.format
plt.rcParams['figure.figsize'] = (12, 8)
# Read the Dataframe from the CSV file
df = pd.read_csv(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\The_500_Largest_Companies_in_USA\Largest_500_Companies.csv')
In [2]:
##### Data Cleaning
# Remove Duplicate data from raw table
df = df.drop_duplicates()
# Drop/remove all entries with blanks
# df.dropna(subset='temperature_2m', inplace=True)
# df.dropna(subset='relative_humidity_2m', inplace=True)
df.dropna(inplace=True)
df
# Check whether there's still any blank rows/columns
df[df.isna().any(axis=1)]
Out[2]:
| Rank | Company | Industry | City | State | Zip Code | Website | Employees | Revenue (rounded) | CEO |
|---|
In [3]:
# Remove $ sign from Column 'Revenue (rounded)'
df['Revenue (rounded)'] = df['Revenue (rounded)'].str.replace('$','')
df['Revenue (rounded)'] = df['Revenue (rounded)'].str.replace(',','')
df['Employees'] = df['Employees'].str.replace(',','')
# Convert the type of Column 'Revenue (rounded)' into Float type
df['Revenue (rounded)'] = df['Revenue (rounded)'].astype(float)
# Convert the type of Column 'Employees' into Int type
df['Employees'] = df['Employees'].astype(int)
# Convert the type of Column 'Zip Code' into String type
df['Zip Code'] = df['Zip Code'].astype(str)
df['Zip Code'] = df['Zip Code'].str.zfill(5)
# Drop Column 'Rank' coz we don't need it
df.drop('Rank', axis=1, inplace=True)
In [4]:
df.head(2).style.format({'Employees': '{:,.0f}', 'Revenue (rounded)': '{:,.2f}'})
Out[4]:
| Company | Industry | City | State | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | Walmart | General Merchandisers | Bentonville | Arkansas | 72712 | walmart.com | 2,100,000 | 681,000,000,000.00 | Douglas McMillon |
| 1 | Amazon | Internet Services and Retailing | Seattle | Washington | 98109 | amazon.com | 1,556,000 | 638,000,000,000.00 | Andrew Jassy |
In [5]:
# Check whether there's still ZipCodes that less than 5 in length.
for index, row in df.iterrows():
if len(row['Zip Code']) < 5:
print("Ada yang panjangnya kurang dari 5")
# To mark that the For loop has finished.
print("Finished")
Finished
In [6]:
# Map of States in USA
gdfsts = gpd.read_file(r"C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\110m_cultural\ne_110m_admin_1_states_provinces.shp")
gdfsts = gdfsts.query("name != 'Hawaii'")
gdfsts = gdfsts.query("name != 'Alaska'")
gdfsts = gdfsts.rename(columns={'name': 'State'})
gdfsts = gdfsts[['State','region','postal','latitude','longitude','geometry']]
In [7]:
gdfsts.explore(column='State', cmap='hsv', edgecolor = 'black', legend=False)
Out[7]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [8]:
# Draw the States Map of Fortune500 Companies
gdfsts500 = gdfsts.merge(df, how = 'inner', on = ['State'])
gdfsts500.explore(column='State', cmap='hsv', edgecolor='black', legend=False)
Out[8]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [9]:
# Sneak peek at GeoDataframe of Fortune500 Companies
gdfsts500.head(2)
Out[9]:
| State | region | postal | latitude | longitude | geometry | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | UnitedHealth | Health Care: Insurance and Managed Care | Eden Prairie | 55344 | unitedhealthgroup.com | 400000 | 400,300,000,000 | Stephen Hemsley |
| 1 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Target | General Merchandisers | Minneapolis | 55403 | target.com | 440000 | 106,600,000,000 | Brian Cornell |
Draw the Map of Cities in Fortune500 Dataset¶
In [10]:
dfusact = pd.read_excel(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\simplemaps_uszips_basicv1.91\uszips.xlsx', sheet_name='ZIP2')
# Convert the type of Column 'Zip Code' into String type
#dfusact['Zip Code'] = dfusact['Zip Code'].astype(int)
dfusact['Zip Code'] = dfusact['Zip Code'].astype(str)
dfusact['Zip Code'] = dfusact['Zip Code'].str.replace('.0','')
dfusact['Zip Code'] = dfusact['Zip Code'].str.zfill(5)
dfusact.head(2)
Out[10]:
| Zip Code | Latitude | Longitude | Population | |
|---|---|---|---|---|
| 0 | 00601 | 18 | -67 | 16,721 |
| 1 | 00602 | 18 | -67 | 37,510 |
In [11]:
# Check Data Types of Geo location data
In [12]:
type(dfusact['Latitude'][0])
Out[12]:
numpy.float64
In [13]:
type(dfusact['Longitude'][0])
Out[13]:
numpy.float64
In [14]:
type(dfusact['Zip Code'][0])
Out[14]:
str
In [15]:
# Create geometry column
geometry = gpd.points_from_xy(dfusact['Longitude'], dfusact['Latitude'], crs="EPSG:4326")
# Create GeoDataFrame
gdfusact = gpd.GeoDataFrame(dfusact, geometry=geometry)
In [16]:
# Check the data type of 'geometry' Column
type(gdfusact['geometry'])
Out[16]:
geopandas.geoseries.GeoSeries
In [17]:
# Create Geodataframe of the Fortune500 cities with joining 'df' Dataframe with 'gdfusact' Dataframe
#gdfusact500 = gdfusact.merge(df, how = 'inner', on = ['City','State'])
gdfusact500 = gdfusact.merge(df, how = 'inner', on = ['Zip Code'])
# Let's explore one of the City in Fortune500 list
gdfusact500.where(gdfusact500['Zip Code'] == '44143').dropna().style.format({'Employees': '{:,.0f}', 'Revenue (rounded)': '{:,.2f}'})
Out[17]:
| Zip Code | Latitude | Longitude | Population | geometry | Company | Industry | City | State | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 218 | 44143 | 41.553580 | -81.475130 | 24337.000000 | POINT (-81.47513 41.55358) | Progressive | Insurance: Property and Casualty (Stock) | Mayfield Village | Ohio | progressive.com | 66,300 | 75,400,000,000.00 | Susan Patricia Griffith |
In [18]:
# How Mayfield Village looks like
gdfusact500.query("City == 'Mayfield Village'").explore()
Out[18]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [19]:
# US Fortune500 Companies Map (2025) color mapped by Population Column.
gdfusact500.explore(column='Population', name='Cities in Fortune500',cmap='RdYlGn')
Out[19]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [20]:
# Conclusion: Fortune500 Companies are mostly located on Eastern half of mainland USA.
In [ ]:
In [21]:
gdf2 = gpd.read_file(r"C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\nyc-zip-code-tabulation-areas-polygons.geojson")
gdf2
Out[21]:
| OBJECTID | postalCode | PO_NAME | STATE | borough | ST_FIPS | CTY_FIPS | BLDGpostalCode | Shape_Leng | Shape_Area | @id | geometry | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 11372 | Jackson Heights | NY | Queens | 36 | 081 | 0 | 20,625 | 20,163,284 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.86942 40.74916, -73.89507 40.746... |
| 1 | 2 | 11004 | Glen Oaks | NY | Queens | 36 | 081 | 0 | 23,003 | 22,606,527 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.71068 40.75004, -73.70869 40.748... |
| 2 | 3 | 11040 | New Hyde Park | NY | Queens | 36 | 081 | 0 | 15,749 | 6,269,333 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.70098 40.7389, -73.70309 40.7445... |
| 3 | 4 | 11426 | Bellerose | NY | Queens | 36 | 081 | 0 | 35,933 | 49,418,364 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.7227 40.75373, -73.72251 40.7533... |
| 4 | 5 | 11365 | Fresh Meadows | NY | Queens | 36 | 081 | 0 | 38,694 | 69,385,866 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.81089 40.72717, -73.81116 40.728... |
| 5 | 6 | 11373 | Elmhurst | NY | Queens | 36 | 081 | 0 | 33,756 | 42,659,400 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88722 40.72753, -73.88723 40.728... |
| 6 | 7 | 11001 | Floral Park | NY | Queens | 36 | 081 | 0 | 13,595 | 9,155,180 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.70098 40.7389, -73.6996 40.73959... |
| 7 | 8 | 11375 | Forest Hills | NY | Queens | 36 | 081 | 0 | 36,277 | 55,587,772 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.85625 40.73672, -73.85205 40.737... |
| 8 | 9 | 11427 | Queens Village | NY | Queens | 36 | 081 | 0 | 31,232 | 39,568,339 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.74169 40.73682, -73.73568 40.738... |
| 9 | 10 | 11374 | Rego Park | NY | Queens | 36 | 081 | 0 | 26,324 | 25,203,459 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.86451 40.73407, -73.85872 40.735... |
| 10 | 11 | 11366 | Fresh Meadows | NY | Queens | 36 | 081 | 0 | 27,283 | 20,358,593 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.77011 40.73178, -73.7751 40.7308... |
| 11 | 12 | 11423 | Hollis | NY | Queens | 36 | 081 | 0 | 31,340 | 45,095,032 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.77011 40.73178, -73.76536 40.725... |
| 12 | 13 | 11428 | Queens Village | NY | Queens | 36 | 081 | 0 | 22,516 | 21,985,773 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.72775 40.72258, -73.72762 40.722... |
| 13 | 14 | 11432 | Jamaica | NY | Queens | 36 | 081 | 0 | 33,124 | 60,177,576 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.80904 40.71991, -73.79288 40.725... |
| 14 | 15 | 11379 | Middle Village | NY | Queens | 36 | 081 | 0 | 33,528 | 57,537,331 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8719 40.72686, -73.87182 40.7267... |
| 15 | 16 | 11429 | Queens Village | NY | Queens | 36 | 081 | 0 | 26,527 | 39,559,398 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.72848 40.72077, -73.72793 40.719... |
| 16 | 17 | 11435 | Jamaica | NY | Queens | 36 | 081 | 0 | 34,404 | 42,105,899 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.82606 40.7154, -73.82306 40.7161... |
| 17 | 18 | 11415 | Kew Gardens | NY | Queens | 36 | 081 | 0 | 21,075 | 16,802,280 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.82606 40.7154, -73.82348 40.7123... |
| 18 | 19 | 11418 | Richmond Hill | NY | Queens | 36 | 081 | 0 | 31,854 | 32,025,131 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83715 40.70796, -73.83655 40.708... |
| 19 | 20 | 11433 | Jamaica | NY | Queens | 36 | 081 | 0 | 30,604 | 47,739,433 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.77968 40.7086, -73.77937 40.7078... |
| 20 | 21 | 11451 | Jamaica | NY | Queens | 36 | 081 | 0 | 2,962 | 487,600 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.80157 40.70121, -73.79887 40.702... |
| 21 | 22 | 11221 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 30,948 | 38,580,480 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93822 40.68389, -73.94389 40.683... |
| 22 | 23 | 11421 | Woodhaven | NY | Queens | 36 | 081 | 0 | 22,224 | 24,314,442 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8492 40.69827, -73.84741 40.6957... |
| 23 | 24 | 11419 | South Richmond Hill | NY | Queens | 36 | 081 | 0 | 23,069 | 31,278,858 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83754 40.69136, -73.82812 40.694... |
| 24 | 25 | 11434 | Jamaica | NY | Queens | 36 | 081 | 0 | 43,830 | 87,379,704 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.76989 40.69631, -73.76605 40.692... |
| 25 | 26 | 11216 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 26,473 | 26,478,229 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94564 40.69203, -73.94389 40.683... |
| 26 | 27 | 11416 | Ozone Park | NY | Queens | 36 | 081 | 0 | 21,631 | 18,854,850 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8443 40.68944, -73.83754 40.6913... |
| 27 | 28 | 11233 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 30,234 | 37,871,694 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93822 40.68389, -73.91785 40.686... |
| 28 | 29 | 11436 | Jamaica | NY | Queens | 36 | 081 | 0 | 20,579 | 22,699,295 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.80585 40.68291, -73.79391 40.686... |
| 29 | 30 | 11213 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 23,899 | 29,631,004 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9374 40.67973, -73.92906 40.6792... |
| 30 | 31 | 11212 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 26,622 | 41,972,104 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.90294 40.67084, -73.90223 40.668... |
| 31 | 32 | 11225 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 23,346 | 23,698,630 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95797 40.67066, -73.95505 40.670... |
| 32 | 33 | 11218 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 30,623 | 36,868,799 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97208 40.6506, -73.9714 40.64826... |
| 33 | 34 | 11226 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 28,636 | 39,408,598 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9619 40.65487, -73.96152 40.6550... |
| 34 | 35 | 11219 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 29,464 | 42,002,738 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98906 40.64412, -73.99193 40.642... |
| 35 | 36 | 11210 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 29,975 | 47,887,023 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9584 40.63633, -73.95374 40.6385... |
| 36 | 37 | 11230 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 31,795 | 49,926,703 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96451 40.63669, -73.96422 40.635... |
| 37 | 38 | 11204 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 30,325 | 43,555,185 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98108 40.63529, -73.98085 40.635... |
| 38 | 39 | 10471 | Bronx | NY | Bronx | 36 | 005 | 0 | 53,209 | 89,651,407 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88192 40.90667, -73.8779 40.9055... |
| 39 | 40 | 10470 | Bronx | NY | Bronx | 36 | 005 | 0 | 32,649 | 21,543,462 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8779 40.90555, -73.87786 40.9059... |
| 40 | 41 | 10466 | Bronx | NY | Bronx | 36 | 005 | 0 | 35,358 | 55,262,491 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.84464 40.90475, -73.84443 40.904... |
| 41 | 42 | 10467 | Bronx | NY | Bronx | 36 | 005 | 0 | 43,945 | 69,336,166 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88011 40.8952, -73.87459 40.8957... |
| 42 | 43 | 10463 | Bronx | NY | Bronx | 36 | 005 | 0 | 47,485 | 36,703,382 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92065 40.88724, -73.92038 40.887... |
| 43 | 44 | 10475 | Bronx | NY | Bronx | 36 | 005 | 0 | 45,028 | 38,633,297 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.82722 40.89093, -73.82511 40.890... |
| 44 | 45 | 10464 | Bronx | NY | Bronx | 36 | 005 | 0 | 95,376 | 76,257,485 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.81539 40.88939, -73.81365 40.888... |
| 45 | 46 | 10469 | Bronx | NY | Bronx | 36 | 005 | 0 | 34,901 | 68,040,887 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.85588 40.88386, -73.85011 40.882... |
| 46 | 47 | 10468 | Bronx | NY | Bronx | 36 | 005 | 0 | 37,083 | 34,447,605 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88701 40.88247, -73.88592 40.880... |
| 47 | 48 | 10463 | Bronx | NY | Manhattan | 36 | 061 | 0 | 7,792 | 3,119,702 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.91544 40.87559, -73.91509 40.876... |
| 48 | 49 | 10458 | Bronx | NY | Bronx | 36 | 005 | 0 | 29,391 | 35,968,813 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8848 40.87846, -73.88423 40.8787... |
| 49 | 50 | 10034 | New York | NY | Manhattan | 36 | 061 | 0 | 28,234 | 24,503,892 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92062 40.873, -73.92004 40.87328... |
| 50 | 51 | 10033 | New York | NY | Manhattan | 36 | 061 | 0 | 29,416 | 16,156,054 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93213 40.86945, -73.93128 40.868... |
| 51 | 52 | 10462 | Bronx | NY | Bronx | 36 | 005 | 0 | 49,496 | 53,022,514 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.84218 40.83537, -73.83915 40.835... |
| 52 | 53 | 10040 | New York | NY | Manhattan | 36 | 061 | 0 | 24,555 | 16,340,743 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93379 40.86307, -73.93298 40.865... |
| 53 | 54 | 10453 | Bronx | NY | Bronx | 36 | 005 | 0 | 26,399 | 25,748,509 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89995 40.85742, -73.90134 40.855... |
| 54 | 55 | 10465 | Bronx | NY | Bronx | 36 | 005 | 0 | 96,349 | 108,423,743 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83915 40.83568, -73.83869 40.835... |
| 55 | 56 | 10464 | Bronx | NY | Bronx | 36 | 005 | 0 | 14,922 | 4,512,531 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.772 40.85712, -73.77204 40.85894... |
| 56 | 57 | 10464 | Bronx | NY | Bronx | 36 | 005 | 0 | 26,774 | 11,587,954 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.79235 40.85607, -73.79204 40.855... |
| 57 | 58 | 10461 | Bronx | NY | Bronx | 36 | 005 | 0 | 35,943 | 62,824,058 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.84218 40.83537, -73.84543 40.834... |
| 58 | 59 | 10457 | Bronx | NY | Bronx | 36 | 005 | 0 | 29,927 | 37,640,607 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89995 40.85742, -73.89573 40.856... |
| 59 | 60 | 10460 | Bronx | NY | Bronx | 36 | 005 | 0 | 41,386 | 35,155,667 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.87687 40.85539, -73.87732 40.854... |
| 60 | 61 | 10032 | New York | NY | Manhattan | 36 | 061 | 0 | 31,658 | 23,159,566 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94692 40.85053, -73.94258 40.849... |
| 61 | 62 | 10452 | Bronx | NY | Bronx | 36 | 005 | 0 | 24,379 | 27,550,386 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9281 40.84532, -73.92732 40.8464... |
| 62 | 63 | 10456 | Bronx | NY | Bronx | 36 | 005 | 0 | 30,925 | 29,933,452 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.91314 40.83981, -73.91208 40.839... |
| 63 | 64 | 10472 | Bronx | NY | Bronx | 36 | 005 | 0 | 27,006 | 30,963,245 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88011 40.83723, -73.87747 40.836... |
| 64 | 65 | 10031 | New York | NY | Manhattan | 36 | 061 | 0 | 23,228 | 16,902,152 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94009 40.83035, -73.93968 40.829... |
| 65 | 66 | 10039 | New York | NY | Manhattan | 36 | 061 | 0 | 15,005 | 8,419,028 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9344 40.8361, -73.93492 40.83519... |
| 66 | 67 | 10459 | Bronx | NY | Bronx | 36 | 005 | 0 | 24,994 | 22,551,941 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8963 40.83354, -73.89477 40.8343... |
| 67 | 68 | 10451 | Bronx | NY | Bronx | 36 | 005 | 0 | 32,574 | 28,944,107 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93294 40.82772, -73.93311 40.828... |
| 68 | 69 | 10473 | Bronx | NY | Bronx | 36 | 005 | 0 | 46,333 | 59,522,355 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.847 40.828, -73.8458 40.82832, -... |
| 69 | 70 | 10030 | New York | NY | Manhattan | 36 | 061 | 0 | 11,274 | 7,757,661 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93623 40.82044, -73.9418 40.8128... |
| 70 | 71 | 10027 | New York | NY | Manhattan | 36 | 061 | 0 | 31,598 | 24,695,279 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96569 40.80903, -73.96442 40.810... |
| 71 | 72 | 10474 | Bronx | NY | Bronx | 36 | 005 | 0 | 30,197 | 40,614,090 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89543 40.81584, -73.89332 40.817... |
| 72 | 73 | 10455 | Bronx | NY | Bronx | 36 | 005 | 0 | 26,038 | 19,846,919 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.90337 40.81878, -73.9016 40.8196... |
| 73 | 74 | 10037 | New York | NY | Manhattan | 36 | 061 | 0 | 12,512 | 7,188,981 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93382 40.8195, -73.93381 40.8156... |
| 74 | 75 | 10024 | New York | NY | Manhattan | 36 | 061 | 0 | 40,064 | 22,877,335 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9659 40.80881, -73.96689 40.8077... |
| 75 | 76 | 10454 | Bronx | NY | Bronx | 36 | 005 | 0 | 25,984 | 31,063,613 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93176 40.80793, -73.93062 40.808... |
| 76 | 77 | 10026 | New York | NY | Manhattan | 36 | 061 | 0 | 15,645 | 11,092,681 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9446 40.80323, -73.94922 40.7969... |
| 77 | 78 | 10035 | New York | NY | Manhattan | 36 | 061 | 0 | 17,087 | 15,445,657 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93326 40.80724, -73.93129 40.805... |
| 78 | 79 | 10025 | New York | NY | Manhattan | 36 | 061 | 0 | 20,734 | 19,631,044 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95936 40.80612, -73.95983 40.805... |
| 79 | 80 | 10035 | New York | NY | Manhattan | 36 | 061 | 0 | 25,010 | 23,494,871 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92742 40.79839, -73.92694 40.799... |
| 80 | 81 | 11357 | Whitestone | NY | Queens | 36 | 081 | 0 | 44,133 | 77,359,111 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.82482 40.79715, -73.82423 40.797... |
| 81 | 82 | 10029 | New York | NY | Manhattan | 36 | 061 | 0 | 19,647 | 22,963,436 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94646 40.80067, -73.93092 40.794... |
| 82 | 83 | 00083 | Central Park | NY | Manhattan | 36 | 061 | 0 | 32,711 | 38,300,990 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94922 40.79691, -73.97301 40.764... |
| 83 | 84 | 11356 | College Point | NY | Queens | 36 | 081 | 0 | 39,906 | 43,321,159 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.85465 40.78943, -73.85447 40.790... |
| 84 | 85 | 11359 | Bayside | NY | Queens | 36 | 081 | 0 | 12,842 | 6,567,982 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.78178 40.79485, -73.78323 40.794... |
| 85 | 86 | 11360 | Bayside | NY | Queens | 36 | 081 | 0 | 31,491 | 38,834,824 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.78664 40.79032, -73.78389 40.790... |
| 86 | 87 | 11105 | Astoria | NY | Queens | 36 | 081 | 0 | 36,788 | 48,795,608 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89672 40.78294, -73.89618 40.783... |
| 87 | 88 | 10128 | New York | NY | Manhattan | 36 | 061 | 0 | 15,005 | 11,011,682 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94359 40.78283, -73.94388 40.781... |
| 88 | 89 | 11371 | Flushing | NY | Queens | 36 | 081 | 0 | 33,739 | 30,558,475 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.8851 40.77846, -73.88525 40.7786... |
| 89 | 90 | 10023 | New York | NY | Manhattan | 36 | 061 | 0 | 22,471 | 15,212,713 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99307 40.77434, -73.98964 40.772... |
| 90 | 91 | 11363 | Little Neck | NY | Queens | 36 | 081 | 0 | 27,323 | 24,242,790 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.75506 40.77646, -73.75483 40.776... |
| 91 | 92 | 10028 | New York | NY | Manhattan | 36 | 061 | 0 | 18,177 | 9,842,046 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95992 40.78221, -73.94663 40.776... |
| 92 | 93 | 11354 | Flushing | NY | Queens | 36 | 081 | 0 | 44,429 | 61,985,147 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.84282 40.76615, -73.84287 40.765... |
| 93 | 94 | 11102 | Astoria | NY | Queens | 36 | 081 | 0 | 21,057 | 19,116,258 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92828 40.7769, -73.92398 40.7746... |
| 94 | 95 | 11370 | East Elmhurst | NY | Queens | 36 | 081 | 0 | 28,831 | 23,600,231 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89144 40.77636, -73.89145 40.776... |
| 95 | 96 | 10021 | New York | NY | Manhattan | 36 | 061 | 0 | 14,364 | 10,495,133 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94908 40.76828, -73.95232 40.764... |
| 96 | 97 | 11361 | Bayside | NY | Queens | 36 | 081 | 0 | 33,141 | 50,163,518 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.76642 40.77595, -73.76574 40.774... |
| 97 | 98 | 11358 | Flushing | NY | Queens | 36 | 081 | 0 | 31,560 | 54,622,541 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.80389 40.7749, -73.79276 40.7740... |
| 98 | 99 | 11362 | Little Neck | NY | Queens | 36 | 081 | 0 | 34,988 | 54,680,551 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.75195 40.76336, -73.74749 40.764... |
| 99 | 100 | 10044 | New York | NY | Manhattan | 36 | 061 | 0 | 21,449 | 6,296,113 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96025 40.7516, -73.9593 40.75328... |
| 100 | 101 | 11369 | East Elmhurst | NY | Queens | 36 | 081 | 0 | 25,542 | 30,060,493 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88782 40.76721, -73.88589 40.767... |
| 101 | 102 | 11103 | Astoria | NY | Queens | 36 | 081 | 0 | 21,849 | 20,222,395 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.91431 40.77152, -73.91167 40.769... |
| 102 | 103 | 11106 | Astoria | NY | Queens | 36 | 081 | 0 | 22,169 | 23,866,113 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93446 40.77118, -73.93421 40.771... |
| 103 | 104 | 11368 | Corona | NY | Queens | 36 | 081 | 0 | 51,118 | 72,489,663 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.86264 40.76689, -73.86272 40.766... |
| 104 | 105 | 11377 | Woodside | NY | Queens | 36 | 081 | 0 | 46,887 | 71,832,387 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.90203 40.76742, -73.89308 40.765... |
| 105 | 106 | 10036 | New York | NY | Manhattan | 36 | 061 | 0 | 16,419 | 11,395,111 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98134 40.75865, -73.97812 40.757... |
| 106 | 107 | 11355 | Flushing | NY | Queens | 36 | 081 | 0 | 33,070 | 49,383,079 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83787 40.75448, -73.8338 40.7567... |
| 107 | 108 | 11101 | Long Island City | NY | Queens | 36 | 081 | 0 | 55,297 | 79,311,463 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92246 40.75743, -73.91467 40.753... |
| 108 | 109 | 11364 | Oakland Gardens | NY | Queens | 36 | 081 | 0 | 37,489 | 84,259,665 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.77981 40.7519, -73.77618 40.7528... |
| 109 | 110 | 10018 | New York | NY | Manhattan | 36 | 061 | 0 | 19,510 | 10,705,796 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.0017 40.76138, -73.99396 40.7582... |
| 110 | 111 | 10020 | New York | NY | Manhattan | 36 | 061 | 0 | 3,612 | 697,297 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9772 40.75854, -73.97812 40.7572... |
| 111 | 112 | 11005 | Floral Park | NY | Queens | 36 | 081 | 0 | 15,261 | 9,075,527 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.71291 40.75995, -73.71239 40.759... |
| 112 | 113 | 10017 | New York | NY | Manhattan | 36 | 061 | 0 | 14,309 | 9,794,383 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97765 40.75791, -73.9653 40.7526... |
| 113 | 114 | 10001 | New York | NY | Manhattan | 36 | 061 | 0 | 19,254 | 17,794,941 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00827 40.75259, -74.00763 40.754... |
| 114 | 115 | 10011 | New York | NY | Manhattan | 36 | 061 | 0 | 24,714 | 18,118,417 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99232 40.74357, -73.99416 40.741... |
| 115 | 116 | 10016 | New York | NY | Manhattan | 36 | 061 | 0 | 18,193 | 15,042,403 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98182 40.7522, -73.97078 40.7475... |
| 116 | 117 | 11104 | Sunnyside | NY | Queens | 36 | 081 | 0 | 21,699 | 12,084,432 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.90984 40.75162, -73.90944 40.750... |
| 117 | 118 | 11109 | Long Island City | NY | Queens | 36 | 081 | 0 | 2,453 | 231,863 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95946 40.74409, -73.95938 40.744... |
| 118 | 119 | 10010 | New York | NY | Manhattan | 36 | 061 | 0 | 23,513 | 9,768,395 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98775 40.74407, -73.98453 40.742... |
| 119 | 120 | 11367 | Flushing | NY | Queens | 36 | 081 | 0 | 33,506 | 72,810,152 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83761 40.74324, -73.83516 40.743... |
| 120 | 121 | 10014 | New York | NY | Manhattan | 36 | 061 | 0 | 20,454 | 14,151,052 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00095 40.73171, -74.00214 40.729... |
| 121 | 122 | 10003 | New York | NY | Manhattan | 36 | 061 | 0 | 17,396 | 15,538,376 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97986 40.73497, -73.98864 40.722... |
| 122 | 123 | 11222 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 32,221 | 42,904,554 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96166 40.72587, -73.96109 40.729... |
| 123 | 124 | 10002 | New York | NY | Manhattan | 36 | 061 | 0 | 36,484 | 26,280,129 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97442 40.73642, -73.9745 40.7356... |
| 124 | 125 | 11378 | Maspeth | NY | Queens | 36 | 081 | 0 | 42,329 | 66,342,001 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92421 40.73552, -73.92277 40.734... |
| 125 | 126 | 10009 | New York | NY | Manhattan | 36 | 061 | 0 | 16,247 | 15,903,520 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97346 40.73071, -73.97249 40.729... |
| 126 | 127 | 10012 | New York | NY | Manhattan | 36 | 061 | 0 | 12,423 | 9,193,739 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99657 40.72955, -73.99155 40.727... |
| 127 | 128 | 10013 | New York | NY | Manhattan | 36 | 061 | 0 | 19,248 | 15,580,578 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00373 40.72625, -74.00457 40.724... |
| 128 | 129 | 11211 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 50,607 | 58,162,525 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92919 40.72465, -73.92941 40.724... |
| 129 | 130 | 10007 | New York | NY | Manhattan | 36 | 061 | 0 | 13,425 | 5,328,635 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01362 40.71631, -74.01339 40.717... |
| 130 | 131 | 11237 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 30,773 | 27,373,778 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92817 40.71421, -73.92409 40.713... |
| 131 | 132 | 11385 | Ridgewood | NY | Queens | 36 | 081 | 0 | 67,619 | 125,023,075 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.92409 40.71396, -73.90031 40.712... |
| 132 | 133 | 10038 | New York | NY | Manhattan | 36 | 061 | 0 | 12,605 | 7,022,761 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99923 40.70787, -73.99979 40.707... |
| 133 | 134 | 11206 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 28,571 | 40,680,015 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9348 40.71337, -73.93228 40.7077... |
| 134 | 135 | 10006 | New York | NY | Manhattan | 36 | 061 | 0 | 6,795 | 1,716,641 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01123 40.71037, -74.00999 40.709... |
| 135 | 136 | 11412 | Saint Albans | NY | Queens | 36 | 081 | 0 | 29,899 | 46,687,804 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.75047 40.70564, -73.74528 40.694... |
| 136 | 137 | 10005 | New York | NY | Manhattan | 36 | 061 | 0 | 6,384 | 2,082,901 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00597 40.70432, -74.00777 40.703... |
| 137 | 138 | 11251 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 31,556 | 10,379,322 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97556 40.69952, -73.97537 40.699... |
| 138 | 139 | 10004 | New York | NY | Manhattan | 36 | 061 | 0 | 13,770 | 4,001,782 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00597 40.70432, -74.0058 40.7042... |
| 139 | 140 | 11411 | Cambria Heights | NY | Queens | 36 | 081 | 0 | 27,775 | 35,889,597 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.72466 40.70581, -73.72465 40.687... |
| 140 | 141 | 11201 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 41,924 | 41,094,887 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99804 40.69877, -74.00002 40.699... |
| 141 | 142 | 10004 | New York | NY | Manhattan | 36 | 061 | 0 | 6,450 | 1,202,708 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.04166 40.69645, -74.04368 40.698... |
| 142 | 143 | 11205 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 22,054 | 23,159,721 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95335 40.69934, -73.95132 40.689... |
| 143 | 144 | 11208 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 49,932 | 79,294,685 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.86632 40.68336, -73.86603 40.681... |
| 144 | 145 | 11207 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 48,842 | 73,742,269 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.90368 40.69046, -73.90211 40.692... |
| 145 | 146 | 10004 | New York | NY | Manhattan | 36 | 061 | 0 | 12,620 | 7,679,616 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.02418 40.68392, -74.0253 40.6840... |
| 146 | 147 | 10004 | New York | NY | Manhattan | 36 | 061 | 0 | 3,246 | 670,708 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.04699 40.69012, -74.04723 40.690... |
| 147 | 148 | 11413 | Springfield Gardens | NY | Queens | 36 | 081 | 0 | 54,283 | 85,392,925 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.73365 40.68554, -73.73222 40.685... |
| 148 | 149 | 11217 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 22,011 | 21,648,158 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97313 40.68962, -73.97269 40.687... |
| 149 | 150 | 11238 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 26,935 | 29,429,423 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95702 40.67329, -73.95797 40.670... |
| 150 | 151 | 11231 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 45,957 | 39,379,691 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98999 40.68332, -73.9913 40.6814... |
| 151 | 152 | 11422 | Rosedale | NY | Queens | 36 | 081 | 0 | 55,579 | 60,091,179 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.72476 40.68743, -73.72461 40.687... |
| 152 | 153 | 11420 | South Ozone Park | NY | Queens | 36 | 081 | 0 | 33,735 | 61,879,568 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.80795 40.68707, -73.80155 40.673... |
| 153 | 154 | 11417 | Ozone Park | NY | Queens | 36 | 081 | 0 | 26,925 | 31,099,087 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83427 40.68533, -73.83352 40.683... |
| 154 | 155 | 11215 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 37,187 | 61,922,822 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98853 40.67955, -73.97042 40.672... |
| 155 | 156 | 11414 | Howard Beach | NY | Queens | 36 | 081 | 0 | 62,133 | 63,974,665 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83339 40.66678, -73.83291 40.666... |
| 156 | 157 | 11231 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 5,642 | 701,979 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01658 40.66476, -74.01726 40.665... |
| 157 | 158 | 11232 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 64,231 | 55,879,065 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99841 40.67131, -73.99633 40.667... |
| 158 | 159 | 11430 | Jamaica | NY | Queens | 36 | 081 | 0 | 103,039 | 199,913,664 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.78941 40.66684, -73.7896 40.6657... |
| 159 | 160 | 11203 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 32,800 | 60,644,835 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9427 40.66406, -73.93716 40.6637... |
| 160 | 161 | 11239 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 36,129 | 41,794,661 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.86623 40.65876, -73.86599 40.658... |
| 161 | 162 | 11236 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 44,837 | 96,373,992 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89888 40.65646, -73.89873 40.655... |
| 162 | 163 | 11220 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 39,989 | 47,453,786 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.02449 40.65092, -74.01867 40.647... |
| 163 | 164 | 10301 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 79,639 | 105,182,713 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.08931 40.64733, -74.08764 40.648... |
| 164 | 165 | 10310 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 43,886 | 53,463,275 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.12065 40.64104, -74.11961 40.641... |
| 165 | 166 | 10303 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 54,576 | 81,629,774 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.17843 40.64254, -74.1778 40.6426... |
| 166 | 167 | 11234 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 115,170 | 206,201,040 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.93439 40.63483, -73.93226 40.634... |
| 167 | 168 | 10302 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 27,433 | 29,555,323 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.13926 40.64074, -74.13902 40.640... |
| 168 | 169 | 11693 | Far Rockaway | NY | Queens | 36 | 081 | 0 | 87,509 | 46,471,727 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83205 40.63516, -73.83245 40.635... |
| 169 | 170 | 11209 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 37,123 | 57,842,314 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.03693 40.63873, -74.03596 40.638... |
| 170 | 171 | 10304 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 85,662 | 98,226,680 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.08412 40.63478, -74.08231 40.633... |
| 171 | 172 | 10314 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 126,072 | 473,985,727 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.11967 40.62174, -74.11913 40.620... |
| 172 | 173 | 11693 | Far Rockaway | NY | Brooklyn | 36 | 047 | 0 | 9,480 | 3,497,516 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.84076 40.62536, -73.84306 40.627... |
| 173 | 174 | 11228 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 29,618 | 43,893,025 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01634 40.63029, -74.01605 40.631... |
| 174 | 175 | 11096 | Inwood | NY | Queens | 36 | 081 | 0 | 5,205 | 1,512,446 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.7674 40.61546, -73.76965 40.6156... |
| 175 | 176 | 10305 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 55,570 | 111,441,829 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.06361 40.61655, -74.06139 40.614... |
| 176 | 177 | 11229 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 43,382 | 60,119,326 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94483 40.61605, -73.94457 40.614... |
| 177 | 178 | 11214 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 52,862 | 61,096,539 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98725 40.60724, -73.98255 40.582... |
| 178 | 179 | 11691 | Far Rockaway | NY | Queens | 36 | 081 | 0 | 70,128 | 83,927,815 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.74691 40.61173, -73.74654 40.611... |
| 179 | 180 | 11096 | Inwood | NY | Queens | 36 | 081 | 0 | 1,455 | 111,974 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.74906 40.61181, -73.74729 40.612... |
| 180 | 181 | 11223 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 31,424 | 58,702,923 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97299 40.60881, -73.96238 40.609... |
| 181 | 182 | 11693 | Far Rockaway | NY | Queens | 36 | 081 | 0 | 6,887 | 1,527,599 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.83263 40.60841, -73.83292 40.608... |
| 182 | 183 | 11692 | Arverne | NY | Queens | 36 | 081 | 0 | 31,673 | 23,992,395 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.79277 40.59995, -73.79219 40.600... |
| 183 | 184 | 11235 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 61,355 | 69,053,803 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.959 40.59178, -73.93301 40.59464... |
| 184 | 185 | 11693 | Far Rockaway | NY | Queens | 36 | 081 | 0 | 19,052 | 12,270,917 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.81336 40.59096, -73.81315 40.591... |
| 185 | 186 | 10306 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 83,569 | 174,102,872 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.10179 40.58462, -74.09772 40.581... |
| 186 | 187 | 11694 | Rockaway Park | NY | Queens | 36 | 081 | 0 | 46,740 | 48,101,607 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.81935 40.58787, -73.81953 40.587... |
| 187 | 188 | 11224 | Brooklyn | NY | Brooklyn | 36 | 047 | 0 | 41,730 | 46,701,984 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9665 40.58513, -73.96879 40.5752... |
| 188 | 189 | 10308 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 41,508 | 62,751,042 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.16589 40.56028, -74.165 40.56154... |
| 189 | 190 | 11697 | Breezy Point | NY | Queens | 36 | 081 | 0 | 48,880 | 59,789,761 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.88323 40.56836, -73.88435 40.567... |
| 190 | 191 | 10312 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 65,792 | 169,087,433 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.19938 40.56041, -74.19367 40.565... |
| 191 | 192 | 10309 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 79,039 | 215,835,794 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.21312 40.55861, -74.21264 40.558... |
| 192 | 193 | 10307 | Staten Island | NY | Staten Island | 36 | 085 | 0 | 31,375 | 46,028,383 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.24967 40.51555, -74.24823 40.516... |
| 193 | 194 | 10280 | New York | NY | Manhattan | 36 | 061 | 0 | 8,192 | 2,234,114 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01664 40.71217, -74.01568 40.711... |
| 194 | 195 | 10048 | New York | NY | Manhattan | 36 | 061 | 0 | 4,034 | 972,788 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01441 40.71099, -74.01375 40.713... |
| 195 | 196 | 10279 | New York | NY | Manhattan | 36 | 061 | 1 | 681 | 28,665 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00864 40.7126, -74.00851 40.7127... |
| 196 | 197 | 10165 | New York | NY | Manhattan | 36 | 061 | 1 | 985 | 40,780 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97918 40.75214, -73.9795 40.7522... |
| 197 | 198 | 10168 | New York | NY | Manhattan | 36 | 061 | 1 | 742 | 27,810 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97703 40.7513, -73.97687 40.7512... |
| 198 | 199 | 10055 | New York | NY | Manhattan | 36 | 061 | 1 | 842 | 37,224 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97407 40.75926, -73.9739 40.7595... |
| 199 | 200 | 10105 | New York | NY | Manhattan | 36 | 061 | 1 | 769 | 35,422 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97924 40.76283, -73.97953 40.762... |
| 200 | 201 | 10118 | New York | NY | Manhattan | 36 | 061 | 1 | 1,393 | 91,734 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98673 40.74857, -73.98655 40.748... |
| 201 | 202 | 10176 | New York | NY | Manhattan | 36 | 061 | 1 | 590 | 18,289 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9787 40.7555, -73.97848 40.75541... |
| 202 | 203 | 10162 | New York | NY | Manhattan | 36 | 061 | 1 | 625 | 21,035 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95133 40.76931, -73.95165 40.769... |
| 203 | 204 | 10019 | New York | NY | Manhattan | 36 | 061 | 0 | 24,983 | 18,828,383 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9931 40.77273, -73.98477 40.7692... |
| 204 | 205 | 10111 | New York | NY | Manhattan | 36 | 061 | 0 | 1,312 | 103,066 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97845 40.75907, -73.97799 40.759... |
| 205 | 206 | 10170 | New York | NY | Manhattan | 36 | 061 | 1 | 1,000 | 61,793 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97631 40.7525, -73.97651 40.7525... |
| 206 | 207 | 10112 | New York | NY | Manhattan | 36 | 061 | 1 | 521 | 16,701 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97274 40.75707, -73.97257 40.757... |
| 207 | 208 | 10122 | New York | NY | Manhattan | 36 | 061 | 1 | 705 | 23,295 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.9921 40.75177, -73.99161 40.7521... |
| 208 | 209 | 10107 | New York | NY | Manhattan | 36 | 061 | 1 | 717 | 23,030 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98299 40.7663, -73.98281 40.7665... |
| 209 | 210 | 10103 | New York | NY | Manhattan | 36 | 061 | 1 | 1,038 | 62,713 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97724 40.76055, -73.97699 40.760... |
| 210 | 211 | 10153 | New York | NY | Manhattan | 36 | 061 | 1 | 1,210 | 80,340 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97288 40.76411, -73.97164 40.763... |
| 211 | 212 | 10174 | New York | NY | Manhattan | 36 | 061 | 1 | 842 | 44,203 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97574 40.75165, -73.97549 40.751... |
| 212 | 213 | 10166 | New York | NY | Manhattan | 36 | 061 | 1 | 1,364 | 110,439 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97728 40.75351, -73.97681 40.754... |
| 213 | 214 | 10169 | New York | NY | Manhattan | 36 | 061 | 1 | 1,113 | 66,246 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97669 40.75456, -73.97647 40.754... |
| 214 | 215 | 10167 | New York | NY | Manhattan | 36 | 061 | 1 | 1,209 | 80,926 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97468 40.7543, -73.97553 40.7546... |
| 215 | 216 | 10177 | New York | NY | Manhattan | 36 | 061 | 1 | 646 | 24,688 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97635 40.755, -73.976 40.75548, ... |
| 216 | 217 | 10172 | New York | NY | Manhattan | 36 | 061 | 1 | 1,202 | 79,589 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97388 40.75538, -73.97347 40.755... |
| 217 | 218 | 10171 | New York | NY | Manhattan | 36 | 061 | 1 | 614 | 23,525 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97408 40.75574, -73.97455 40.755... |
| 218 | 219 | 10154 | New York | NY | Manhattan | 36 | 061 | 1 | 1,201 | 79,149 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97236 40.75743, -73.97325 40.757... |
| 219 | 220 | 10152 | New York | NY | Manhattan | 36 | 061 | 1 | 1,005 | 59,925 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97147 40.75849, -73.97184 40.758... |
| 220 | 221 | 10270 | New York | NY | Manhattan | 36 | 061 | 1 | 753 | 31,256 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00822 40.70654, -74.00794 40.706... |
| 221 | 222 | 10104 | New York | NY | Manhattan | 36 | 061 | 1 | 1,295 | 89,722 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97826 40.76005, -73.97835 40.759... |
| 222 | 223 | 10271 | New York | NY | Manhattan | 36 | 061 | 1 | 940 | 49,237 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01021 40.7083, -74.00994 40.7081... |
| 223 | 224 | 10110 | New York | NY | Manhattan | 36 | 061 | 1 | 615 | 21,249 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98162 40.75395, -73.98145 40.754... |
| 224 | 225 | 10175 | New York | NY | Manhattan | 36 | 061 | 1 | 574 | 18,685 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98 40.75441, -73.97943 40.75416,... |
| 225 | 226 | 10151 | New York | NY | Manhattan | 36 | 061 | 1 | 630 | 21,380 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97359 40.76321, -73.97339 40.763... |
| 226 | 227 | 10173 | New York | NY | Manhattan | 36 | 061 | 1 | 1,188 | 25,689 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97928 40.75403, -73.97912 40.753... |
| 227 | 228 | 10178 | New York | NY | Manhattan | 36 | 061 | 1 | 944 | 51,303 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97729 40.7507, -73.97746 40.7504... |
| 228 | 229 | 10119 | New York | NY | Manhattan | 36 | 061 | 1 | 1,679 | 126,393 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99354 40.75145, -73.9932 40.7519... |
| 229 | 230 | 10121 | New York | NY | Manhattan | 36 | 061 | 1 | 1,414 | 115,105 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99213 40.75066, -73.99132 40.750... |
| 230 | 231 | 10115 | New York | NY | Manhattan | 36 | 061 | 0 | 1,075 | 71,720 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96442 40.81076, -73.96402 40.811... |
| 231 | 232 | 10123 | New York | NY | Manhattan | 36 | 061 | 1 | 662 | 16,139 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.99059 40.75176, -73.99043 40.751... |
| 232 | 233 | 10106 | New York | NY | Manhattan | 36 | 061 | 1 | 863 | 31,053 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98119 40.76553, -73.98101 40.765... |
| 233 | 234 | 10158 | New York | NY | Manhattan | 36 | 061 | 1 | 777 | 35,396 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97543 40.74894, -73.97517 40.749... |
| 234 | 235 | 10041 | New York | NY | Manhattan | 36 | 061 | 1 | 1,642 | 162,237 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01025 40.70317, -74.00896 40.703... |
| 235 | 236 | 10120 | New York | NY | Manhattan | 36 | 061 | 1 | 855 | 35,179 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98938 40.75001, -73.98908 40.749... |
| 236 | 237 | 10278 | New York | NY | Manhattan | 36 | 061 | 1 | 1,889 | 206,706 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00476 40.71507, -74.00531 40.715... |
| 237 | 238 | 10155 | New York | NY | Manhattan | 36 | 061 | 1 | 839 | 24,785 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.96844 40.76111, -73.96833 40.761... |
| 238 | 239 | 10022 | New York | NY | Manhattan | 36 | 061 | 0 | 14,672 | 12,728,336 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.97255 40.7649, -73.96268 40.7607... |
| 239 | 240 | 10043 | New York | NY | Manhattan | 36 | 061 | 1 | 789 | 38,262 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00708 40.70387, -74.0075 40.7042... |
| 240 | 241 | 10081 | New York | NY | Manhattan | 36 | 061 | 1 | 778 | 30,241 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00871 40.70749, -74.00949 40.707... |
| 241 | 242 | 10096 | New York | NY | Manhattan | 36 | 061 | 1 | 851 | 42,106 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98302 40.75485, -73.98283 40.755... |
| 242 | 243 | 10097 | New York | NY | Manhattan | 36 | 061 | 1 | 1,170 | 65,826 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98522 40.76265, -73.98412 40.762... |
| 243 | 244 | 10196 | New York | NY | Manhattan | 36 | 061 | 1 | 721 | 32,502 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98243 40.7568, -73.98213 40.7572... |
| 244 | 245 | 10196 | New York | NY | Manhattan | 36 | 061 | 1 | 289 | 3,155 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98133 40.75673, -73.98128 40.756... |
| 245 | 246 | 10275 | New York | NY | Manhattan | 36 | 061 | 1 | 885 | 48,280 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01451 40.70555, -74.01425 40.706... |
| 246 | 247 | 10265 | New York | NY | Manhattan | 36 | 061 | 1 | 529 | 17,229 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00806 40.70489, -74.00831 40.705... |
| 247 | 248 | 10045 | New York | NY | Manhattan | 36 | 061 | 1 | 1,051 | 47,809 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.0091 40.70877, -74.00886 40.7089... |
| 248 | 249 | 10047 | New York | NY | Manhattan | 36 | 061 | 1 | 545 | 10,150 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98633 40.73958, -73.98599 40.739... |
| 249 | 250 | 10047 | New York | NY | Manhattan | 36 | 061 | 1 | 545 | 10,150 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98633 40.73958, -73.98599 40.739... |
| 250 | 251 | 10080 | New York | NY | Manhattan | 36 | 061 | 1 | 1,313 | 77,111 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01288 40.71052, -74.01259 40.710... |
| 251 | 252 | 10203 | New York | NY | Manhattan | 36 | 061 | 1 | 910 | 37,227 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01194 40.7072, -74.01166 40.7076... |
| 252 | 253 | 10259 | New York | NY | Manhattan | 36 | 061 | 1 | 620 | 21,064 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01036 40.70877, -74.01024 40.708... |
| 253 | 254 | 10260 | New York | NY | Manhattan | 36 | 061 | 1 | 980 | 52,515 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00908 40.70626, -74.0087 40.7066... |
| 254 | 255 | 10285 | New York | NY | Manhattan | 36 | 061 | 1 | 1,068 | 67,350 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01476 40.71309, -74.0155 40.7134... |
| 255 | 256 | 10286 | New York | NY | Manhattan | 36 | 061 | 1 | 438 | 11,264 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.00936 40.70642, -74.00911 40.706... |
| 256 | 257 | 11370 | Bronx | NY | Bronx | 36 | 005 | 0 | 17,838 | 18,190,205 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.89262 40.79246, -73.89274 40.792... |
| 257 | 258 | 10065 | New York | NY | Manhattan | 36 | 061 | 0 | 15,542 | 11,442,580 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.95232 40.76454, -73.95442 40.762... |
| 258 | 259 | 10075 | New York | NY | Manhattan | 36 | 061 | 0 | 13,541 | 4,809,655 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.94908 40.76828, -73.95052 40.768... |
| 259 | 260 | 10069 | New York | NY | Manhattan | 36 | 061 | 0 | 7,781 | 2,372,366 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-73.98821 40.78123, -73.98675 40.780... |
| 260 | 261 | 10281 | New York | NY | Manhattan | 36 | 061 | 0 | 4,717 | 958,087 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01468 40.7098, -74.01638 40.7100... |
| 261 | 262 | 10282 | New York | NY | Manhattan | 36 | 061 | 0 | 6,084 | 1,561,955 | http://nyc.pediacities.com/Resource/PostalCode... | POLYGON ((-74.01323 40.71832, -74.01421 40.713... |
In [22]:
# Check how many Fortune500 Companies are located in New York City (turns out there are 43 Companies)
len(df.query("City == 'New York'"))
Out[22]:
43
In [23]:
# Draw the map of New York City (complete) in detail (interesting due to many Fortune500 Companies are located here)
m = None
m = folium.Map(location = [40.6455, -74.0821], zoom_start=11)
tooltip = folium.features.GeoJsonTooltip(fields=['borough','postalCode'], aliases=["Borough","Postal Code"], labels=True, stick=False)
folium.GeoJson(gdf2, tooltip=tooltip).add_to(m)
folium.LayerControl().add_to(m)
m
Out[23]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [24]:
# Using choropleth to give Color Map to the map.
m = None
m = folium.Map(location = [40.6455, -74.0821], zoom_start=11)
# The second Column for 'columns' (in this case: 'Shape_Leng') option must be numbers (int OR float)
cpleth = folium.Choropleth(gdf2, data=gdf2, key_on='feature.properties.postalCode', columns=['postalCode','Shape_Leng'], fill_color="RdYlGn", legend_name="Borough", name="New York City neighborhoods", line_opacity=1.0)
cpleth.geojson.add_child(tooltip)
cpleth.add_to(m)
folium.LayerControl().add_to(m)
m
Out[24]:
Make this Notebook Trusted to load map: File -> Trust Notebook
Statistics in State Level¶
In [25]:
# Grab all distinct State names
dfsts = df[['State']]
dfsts = dfsts.drop_duplicates()
dfsts = dfsts.reset_index(drop=True)
stslist = dfsts.to_numpy().tolist()
stslist[1][0]
for sts in stslist:
print(sts[0])
print("---------------")
Arkansas --------------- Washington --------------- Minnesota --------------- California --------------- Rhode Island --------------- Nebraska --------------- Texas --------------- Pennsylvania --------------- New York --------------- Connecticut --------------- Ohio --------------- North Carolina --------------- Michigan --------------- Indiana --------------- Missouri --------------- Georgia --------------- District of Columbia --------------- Illinois --------------- Virginia --------------- Kentucky --------------- New Jersey --------------- Tennessee --------------- Idaho --------------- Maryland --------------- Florida --------------- Massachusetts --------------- Oregon --------------- Wisconsin --------------- Colorado --------------- Arizona --------------- Oklahoma --------------- Nevada --------------- Iowa --------------- Louisiana --------------- Delaware --------------- Alabama --------------- Kansas ---------------
In [26]:
gdfsts
Out[26]:
| State | region | postal | latitude | longitude | geometry | |
|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... |
| 1 | Montana | West | MT | 47 | -110 | POLYGON ((-116.04823 49.00037, -113.0595 49.00... |
| 2 | North Dakota | Midwest | ND | 47 | -100 | POLYGON ((-97.22894 49.00089, -97.21414 48.902... |
| 4 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... |
| 5 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... |
| 6 | Arizona | West | AZ | 34 | -112 | POLYGON ((-109.04522 36.99991, -109.04367 31.3... |
| 7 | California | West | CA | 37 | -120 | POLYGON ((-114.64222 35.05311, -114.62212 34.9... |
| 8 | Colorado | West | CO | 39 | -106 | POLYGON ((-102.05017 40.00081, -102.04012 38.4... |
| 9 | Nevada | West | NV | 39 | -117 | POLYGON ((-117.02825 42.00002, -114.03422 41.9... |
| 10 | New Mexico | West | NM | 35 | -106 | POLYGON ((-109.04367 31.3419, -109.04522 36.99... |
| 11 | Oregon | West | OR | 44 | -120 | POLYGON ((-116.915 45.99998, -116.679 45.80736... |
| 12 | Utah | West | UT | 40 | -112 | POLYGON ((-114.03422 41.99312, -111.05024 42.0... |
| 13 | Wyoming | West | WY | 43 | -108 | POLYGON ((-111.08518 44.50615, -111.06719 44.5... |
| 14 | Arkansas | South | AR | 35 | -92 | POLYGON ((-89.66292 36.02307, -89.67351 35.94,... |
| 15 | Iowa | Midwest | IA | 42 | -93 | POLYGON ((-96.45266 43.50179, -95.35994 43.500... |
| 16 | Kansas | Midwest | KS | 38 | -98 | POLYGON ((-102.04118 36.99198, -102.04012 38.4... |
| 17 | Missouri | Midwest | MO | 39 | -92 | POLYGON ((-89.66292 36.02307, -90.31539 36.023... |
| 18 | Nebraska | Midwest | NE | 42 | -100 | POLYGON ((-102.05017 40.00081, -102.05017 40.0... |
| 19 | Oklahoma | South | OK | 35 | -97 | POLYGON ((-103.00322 36.99516, -102.04118 36.9... |
| 20 | South Dakota | Midwest | SD | 44 | -100 | POLYGON ((-96.53945 46.01797, -96.55689 45.872... |
| 21 | Louisiana | South | LA | 31 | -92 | POLYGON ((-94.05976 33.01212, -93.09403 33.010... |
| 22 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... |
| 23 | Connecticut | Northeast | CT | 42 | -73 | POLYGON ((-73.49794 42.05451, -72.73222 42.035... |
| 24 | Massachusetts | Northeast | MA | 42 | -72 | POLYGON ((-71.80091 42.01325, -72.73222 42.035... |
| 25 | New Hampshire | Northeast | NH | 44 | -72 | POLYGON ((-70.81505 42.86519, -70.9336 42.8842... |
| 26 | Rhode Island | Northeast | RI | 42 | -72 | POLYGON ((-71.85383 41.32004, -71.79295 41.466... |
| 27 | Vermont | Northeast | VT | 44 | -73 | POLYGON ((-72.45707 42.72708, -73.28203 42.743... |
| 28 | Alabama | South | AL | 33 | -87 | POLYGON ((-88.16696 34.99967, -86.90968 34.999... |
| 29 | Florida | South | FL | 28 | -82 | POLYGON ((-87.53039 30.2742, -87.45789 30.4112... |
| 30 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... |
| 31 | Mississippi | South | MS | 33 | -90 | POLYGON ((-91.15624 33.01, -91.10808 33.20684,... |
| 32 | South Carolina | South | SC | 34 | -81 | POLYGON ((-80.86501 32.03316, -81.03644 32.084... |
| 33 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... |
| 34 | Indiana | Midwest | IN | 40 | -86 | POLYGON ((-88.05108 37.8196, -88.01881 38.0217... |
| 35 | Kentucky | South | KY | 37 | -86 | POLYGON ((-89.49836 36.5062, -89.27398 36.6115... |
| 36 | North Carolina | South | NC | 36 | -79 | POLYGON ((-83.07637 34.97903, -84.32097 34.986... |
| 37 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... |
| 38 | Tennessee | South | TN | 36 | -86 | POLYGON ((-90.24924 35.02083, -90.13493 35.113... |
| 39 | Virginia | South | VA | 38 | -78 | MULTIPOLYGON (((-83.33059 36.67266, -83.17851 ... |
| 40 | Wisconsin | Midwest | WI | 44 | -90 | POLYGON ((-91.2282 43.50125, -91.25466 43.6139... |
| 41 | West Virginia | South | WV | 39 | -81 | POLYGON ((-81.97254 37.53595, -82.16728 37.554... |
| 42 | Delaware | South | DE | 39 | -75 | POLYGON ((-75.04839 38.44876, -75.71462 38.449... |
| 43 | District of Columbia | South | DC | 39 | -77 | POLYGON ((-77.04124 38.78954, -77.04123 38.789... |
| 44 | Maryland | South | MD | 39 | -77 | POLYGON ((-75.37754 38.01538, -75.37754 38.015... |
| 45 | New Jersey | Northeast | NJ | 40 | -74 | POLYGON ((-75.52781 39.49865, -75.55427 39.691... |
| 46 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... |
| 47 | Pennsylvania | Northeast | PA | 41 | -78 | POLYGON ((-80.51893 40.64111, -80.51627 42.324... |
| 48 | Maine | Northeast | ME | 45 | -69 | POLYGON ((-70.64573 43.09008, -70.75102 43.080... |
| 49 | Michigan | Midwest | MI | 43 | -85 | POLYGON ((-89.95766 47.28691, -89.84283 47.464... |
In [27]:
# Check the Largest Revenue Company in each State
dfmaxrevco = df.head(1)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
mnmaxrev = dfst['Revenue (rounded)'].max()
dfstmaxrevco = dfst.where(dfst['Revenue (rounded)'] == mnmaxrev).dropna()
#dfstmaxrevco[['Rank']] = int(dfstmaxrevco['Rank'].iloc[0])
dfstmaxrevco[['Zip Code']] = int(dfstmaxrevco['Zip Code'].iloc[0])
#print(dfstmaxrevco)
dfmaxrevco = pd.concat([dfmaxrevco, dfstmaxrevco], ignore_index=True)
dfmaxrevco = dfmaxrevco.drop(0)
dfmaxrevco[['State','Company','Industry','City','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[27]:
| State | Company | Industry | City | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | Arkansas | Walmart | General Merchandisers | Bentonville | 72712 | 681,000,000,000 |
| 1 | Washington | Amazon | Internet Services and Retailing | Seattle | 98109 | 638,000,000,000 |
| 2 | Minnesota | UnitedHealth | Health Care: Insurance and Managed Care | Eden Prairie | 55344 | 400,300,000,000 |
| 3 | California | Apple | Computers, Office Equipment | Cupertino | 95014 | 391,000,000,000 |
| 4 | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | Woonsocket | 2895 | 372,800,000,000 |
| 5 | Nebraska | Berkshire Hathaway | Insurance: Property and Casualty (Stock) | Omaha | 68131 | 371,400,000,000 |
| 6 | Texas | Exxon Mobil | Petroleum Refining | Spring | 77389 | 349,600,000,000 |
| 7 | Pennsylvania | Cencora | Wholesalers: Health Care | Conshohocken | 19428 | 294,000,000,000 |
| 8 | New York | JPMorgan Chase | Commercial Banks | New York | 10017 | 278,900,000,000 |
| 9 | Connecticut | Cigna | Health Care: Pharmacy and Other Services | Bloomfield | 6002 | 247,100,000,000 |
| 10 | Ohio | Cardinal Health | Wholesalers: Health Care | Dublin | 43017 | 226,800,000,000 |
| 11 | North Carolina | Bank of America | Commercial Banks | Charlotte | 28255 | 192,400,000,000 |
| 12 | Michigan | General Motors | Motor Vehicles & Parts | Detroit | 48265 | 187,400,000,000 |
| 13 | Indiana | Elevance Health | Health Care: Insurance and Managed Care | Indianapolis | 46204 | 177,000,000,000 |
| 14 | Missouri | Centene | Health Care: Insurance and Managed Care | St. Louis | 63105 | 163,100,000,000 |
| 15 | Georgia | Home Depot | Specialty Retailers: Other | Atlanta | 30339 | 159,500,000,000 |
| 16 | District of Columbia | Fannie Mae | Diversified Financials | Washington | 20005 | 152,700,000,000 |
| 17 | Illinois | Walgreens | Food & Drug Stores | Deerfield | 60015 | 147,700,000,000 |
| 18 | Virginia | Freddie Mac | Diversified Financials | McLean | 22102 | 122,100,000,000 |
| 19 | Kentucky | Humana | Health Care: Insurance and Managed Care | Louisville | 40202 | 117,800,000,000 |
| 20 | New Jersey | Johnson & Johnson | Pharmaceuticals | New Brunswick | 8933 | 88,800,000,000 |
| 21 | Tennessee | FedEx | Mail, Package and Freight Delivery | Memphis | 38120 | 87,700,000,000 |
| 22 | Idaho | Albertsons | Food & Drug Stores | Boise | 83706 | 79,200,000,000 |
| 23 | Maryland | Lockheed Martin | Aerospace & Defense | Bethesda | 20817 | 71,000,000,000 |
| 24 | Florida | Publix Super Markets | Food & Drug Stores | Lakeland | 33811 | 60,200,000,000 |
| 25 | Massachusetts | TJX | Specialty Retailers: Apparel | Framingham | 1701 | 56,400,000,000 |
| 26 | Oregon | Nike | Apparel | Beaverton | 97005 | 51,400,000,000 |
| 27 | Wisconsin | Northwestern Mutual | Insurance: Life, Health (Mutual) | Milwaukee | 53202 | 41,400,000,000 |
| 28 | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | Centennial | 80112 | 27,900,000,000 |
| 29 | Arizona | Freeport-McMoRan | Mining, Crude-Oil Production | Phoenix | 85004 | 25,500,000,000 |
| 30 | Oklahoma | Oneok | Pipelines | Tulsa | 74103 | 21,700,000,000 |
| 31 | Nevada | MGM Resorts International | Hotels, Casinos, Resorts | Las Vegas | 89109 | 17,200,000,000 |
| 32 | Iowa | Principal Financial | Insurance: Life, Health (Stock) | Des Moines | 50392 | 16,100,000,000 |
| 33 | Louisiana | Lumen Technologies | Telecommunications | Monroe | 71203 | 13,100,000,000 |
| 34 | Delaware | DuPont | Chemicals | Wilmington | 19805 | 12,400,000,000 |
| 35 | Alabama | Regions Financial | Commercial Banks | Birmingham | 35203 | 9,400,000,000 |
| 36 | Kansas | Seaboard | Food Production | Merriam | 66202 | 9,100,000,000 |
In [28]:
# Draw the Map of the Largest Revenue Companies in each State
# Join the Dataframe 'gdfsts500' with 'dfmaxrevco'
gdfstsmaxrevco = gdfsts.merge(dfmaxrevco, how = 'inner', on = ['State'])
# ,'Company','Industry','Zip Code','Website','Employees'
gdfstsmaxrevco.head(2)
Out[28]:
| State | region | postal | latitude | longitude | geometry | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | UnitedHealth | Health Care: Insurance and Managed Care | Eden Prairie | 55344 | unitedhealthgroup.com | 400,000 | 400,300,000,000 | Stephen Hemsley |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | Albertsons | Food & Drug Stores | Boise | 83706 | albertsonscompanies.com | 196,600 | 79,200,000,000 | Susan Morris |
In [29]:
m = gdfstsmaxrevco.explore(column='Revenue (rounded)', name='Biggest Revenue Company in each State', cmap='RdYlGn', edgecolor='black', legend_name="Revenue")
folium.LayerControl().add_to(m)
m
Out[29]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [30]:
# Check the Smallest Revenue Company in each State
dfminrevco = df.head(1)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
mnminrev = dfst['Revenue (rounded)'].min()
dfstminrevco = dfst.where(dfst['Revenue (rounded)'] == mnminrev).dropna()
dfstminrevco[['Zip Code']] = int(dfstminrevco['Zip Code'].iloc[0])
dfminrevco = pd.concat([dfminrevco, dfstminrevco], ignore_index=True)
dfminrevco = dfminrevco.drop(0)
dfminrevco[['State','Company','Industry','City','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[30]:
| State | Company | Industry | City | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | Oregon | Lithia Motors | Automotive Retailing, Services | Medford | 97501 | 36,600,000,000 |
| 1 | Idaho | Micron Technology | Semiconductors and Other Electronic Components | Boise | 83716 | 25,100,000,000 |
| 2 | Maryland | Constellation Energy | Energy | Baltimore | 21231 | 23,600,000,000 |
| 3 | Iowa | Casey's General Stores | Specialty Retailers: Other | Ankeny | 50021 | 14,900,000,000 |
| 4 | Nebraska | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | Omaha | 68175 | 14,600,000,000 |
| 5 | Delaware | DuPont | Chemicals | Wilmington | 19805 | 12,400,000,000 |
| 6 | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | Lowell | 72745 | 12,100,000,000 |
| 7 | Louisiana | Entergy | Utilities: Gas and Electric | New Orleans | 70113 | 11,900,000,000 |
| 8 | Nevada | Las Vegas Sands | Hotels, Casinos, Resorts | Las Vegas | 89113 | 11,300,000,000 |
| 9 | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | Reno | 89113 | 11,300,000,000 |
| 10 | North Carolina | Advance Auto Parts | Specialty Retailers: Other | Raleigh | 27609 | 10,900,000,000 |
| 11 | Washington | Expeditors International of Washington | Transportation and Logistics | Bellevue | 98006 | 10,600,000,000 |
| 12 | Washington | Lululemon athletica | Specialty Retailers: Apparel | Sumner | 98006 | 10,600,000,000 |
| 13 | Oklahoma | Williams | Pipelines | Tulsa | 74172 | 10,500,000,000 |
| 14 | Rhode Island | FM | Insurance: Property and Casualty (Stock) | Johnston | 2919 | 10,400,000,000 |
| 15 | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | Wilmington | 1887 | 9,400,000,000 |
| 16 | Tennessee | Eastman Chemical | Chemicals | Kingsport | 37660 | 9,400,000,000 |
| 17 | New Jersey | Zoetis | Pharmaceuticals | Parsippany | 7054 | 9,300,000,000 |
| 18 | Colorado | Ovintiv | Mining, Crude-Oil Production | Denver | 80202 | 9,200,000,000 |
| 19 | Kansas | Seaboard | Food Production | Merriam | 66202 | 9,100,000,000 |
| 20 | District of Columbia | Xylem | Industrial Machinery | Washington | 20003 | 8,600,000,000 |
| 21 | Wisconsin | Rockwell Automation | Electronics, Electrical Equip. | Milwaukee | 53204 | 8,300,000,000 |
| 22 | Connecticut | XPO | Transportation and Logistics | Greenwich | 6831 | 8,100,000,000 |
| 23 | New York | Foot Locker | Specialty Retailers: Apparel | New York | 10169 | 8,000,000,000 |
| 24 | New York | Voya Financial | Diversified Financials | New York | 10169 | 8,000,000,000 |
| 25 | Ohio | TransDigm | Aerospace & Defense | Cleveland | 44115 | 7,900,000,000 |
| 26 | Texas | KBR | Information Technology Services | Houston | 77002 | 7,700,000,000 |
| 27 | Indiana | Zimmer Biomet s | Medical Products and Equipment | Warsaw | 46580 | 7,700,000,000 |
| 28 | Florida | Watsco | Wholesalers: Diversified | Miami | 33133 | 7,600,000,000 |
| 29 | Georgia | Newell Brands | Home Equipment, Furnishings | Atlanta | 30328 | 7,600,000,000 |
| 30 | Arizona | Microchip Technology | Semiconductors and Other Electronic Components | Chandler | 85224 | 7,600,000,000 |
| 31 | Minnesota | Fastenal | Wholesalers: Diversified | Winona | 55987 | 7,500,000,000 |
| 32 | California | Monster Beverage | Beverages | Corona | 92879 | 7,500,000,000 |
| 33 | California | Endeavor | Entertainment | Beverly Hills | 92879 | 7,500,000,000 |
| 34 | Kentucky | Yum Brands | Food Services | Louisville | 40213 | 7,500,000,000 |
| 35 | Virginia | Science Applications International | Information Technology Services | Reston | 20190 | 7,500,000,000 |
| 36 | Michigan | CMS Energy | Utilities: Gas and Electric | Jackson | 49201 | 7,500,000,000 |
| 37 | Pennsylvania | Howmet Aerospace | Aerospace & Defense | Pittsburgh | 15212 | 7,400,000,000 |
| 38 | Missouri | Core & Main | Wholesalers: Diversified | St. Louis | 63146 | 7,400,000,000 |
| 39 | Alabama | Vulcan Materials | Building Materials, Glass | Birmingham | 35242 | 7,400,000,000 |
| 40 | Illinois | Ingredion | Food Production | Westchester | 60154 | 7,400,000,000 |
In [31]:
# Draw the Map of the Smallest Revenue Company in each State
# Join the Dataframe 'gdfsts' with 'dfminrevco'
gdfstsminrevco = gdfsts.merge(dfminrevco, how = 'inner', on = ['State'])
gdfstsminrevco.head(2)
Out[31]:
| State | region | postal | latitude | longitude | geometry | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Fastenal | Wholesalers: Diversified | Winona | 55987 | fastenal.com | 21,000 | 7,500,000,000 | Daniel Florness |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | Micron Technology | Semiconductors and Other Electronic Components | Boise | 83716 | micron.com | 48,000 | 25,100,000,000 | Sanjay Mehrotra |
In [32]:
mminrevco = gdfstsminrevco.explore(column='Revenue (rounded)', name='Smallest Revenue Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mminrevco)
mminrevco
Out[32]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [33]:
# Check the Total Revenue in each State
dfsttr = df.groupby('State')[df.columns[[7]]].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False)
dfsttr
Out[33]:
| Revenue (rounded) | |
|---|---|
| State | |
| Texas | 2,680,800,000,000 |
| California | 2,399,300,000,000 |
| New York | 2,085,200,000,000 |
| Washington | 1,299,400,000,000 |
| Illinois | 1,040,200,000,000 |
| Ohio | 1,035,800,000,000 |
| Minnesota | 802,600,000,000 |
| Arkansas | 764,300,000,000 |
| Virginia | 738,400,000,000 |
| Pennsylvania | 672,400,000,000 |
| Michigan | 602,400,000,000 |
| Georgia | 548,300,000,000 |
| Connecticut | 532,100,000,000 |
| North Carolina | 469,300,000,000 |
| Florida | 448,700,000,000 |
| New Jersey | 440,900,000,000 |
| Rhode Island | 440,300,000,000 |
| Nebraska | 427,000,000,000 |
| Massachusetts | 384,500,000,000 |
| Indiana | 320,500,000,000 |
| Tennessee | 312,700,000,000 |
| Missouri | 262,600,000,000 |
| District of Columbia | 185,200,000,000 |
| Wisconsin | 144,900,000,000 |
| Kentucky | 136,600,000,000 |
| Arizona | 125,000,000,000 |
| Maryland | 119,700,000,000 |
| Colorado | 117,000,000,000 |
| Idaho | 104,300,000,000 |
| Oregon | 88,000,000,000 |
| Oklahoma | 48,100,000,000 |
| Nevada | 39,800,000,000 |
| Iowa | 31,000,000,000 |
| Louisiana | 25,000,000,000 |
| Alabama | 16,800,000,000 |
| Delaware | 12,400,000,000 |
| Kansas | 9,100,000,000 |
In [34]:
# Draw the Map of Total Revenue in each State
# Join the Dataframe 'gdfsts' with 'dfsttr'
gdfststotrevco = gdfsts.merge(dfsttr, how = 'inner', on = ['State'])
gdfststotrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[34]:
| State | region | postal | latitude | longitude | geometry | Revenue (rounded) | |
|---|---|---|---|---|---|---|---|
| 0 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | 2,680,800,000,000 |
| 1 | California | West | CA | 37 | -120 | POLYGON ((-114.64222 35.05311, -114.62212 34.9... | 2,399,300,000,000 |
| 2 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | 2,085,200,000,000 |
| 3 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | 1,299,400,000,000 |
| 4 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | 1,040,200,000,000 |
| 5 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | 1,035,800,000,000 |
| 6 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | 802,600,000,000 |
| 7 | Arkansas | South | AR | 35 | -92 | POLYGON ((-89.66292 36.02307, -89.67351 35.94,... | 764,300,000,000 |
| 8 | Virginia | South | VA | 38 | -78 | MULTIPOLYGON (((-83.33059 36.67266, -83.17851 ... | 738,400,000,000 |
| 9 | Pennsylvania | Northeast | PA | 41 | -78 | POLYGON ((-80.51893 40.64111, -80.51627 42.324... | 672,400,000,000 |
| 10 | Michigan | Midwest | MI | 43 | -85 | POLYGON ((-89.95766 47.28691, -89.84283 47.464... | 602,400,000,000 |
| 11 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | 548,300,000,000 |
| 12 | Connecticut | Northeast | CT | 42 | -73 | POLYGON ((-73.49794 42.05451, -72.73222 42.035... | 532,100,000,000 |
| 13 | North Carolina | South | NC | 36 | -79 | POLYGON ((-83.07637 34.97903, -84.32097 34.986... | 469,300,000,000 |
| 14 | Florida | South | FL | 28 | -82 | POLYGON ((-87.53039 30.2742, -87.45789 30.4112... | 448,700,000,000 |
| 15 | New Jersey | Northeast | NJ | 40 | -74 | POLYGON ((-75.52781 39.49865, -75.55427 39.691... | 440,900,000,000 |
| 16 | Rhode Island | Northeast | RI | 42 | -72 | POLYGON ((-71.85383 41.32004, -71.79295 41.466... | 440,300,000,000 |
| 17 | Nebraska | Midwest | NE | 42 | -100 | POLYGON ((-102.05017 40.00081, -102.05017 40.0... | 427,000,000,000 |
| 18 | Massachusetts | Northeast | MA | 42 | -72 | POLYGON ((-71.80091 42.01325, -72.73222 42.035... | 384,500,000,000 |
| 19 | Indiana | Midwest | IN | 40 | -86 | POLYGON ((-88.05108 37.8196, -88.01881 38.0217... | 320,500,000,000 |
| 20 | Tennessee | South | TN | 36 | -86 | POLYGON ((-90.24924 35.02083, -90.13493 35.113... | 312,700,000,000 |
| 21 | Missouri | Midwest | MO | 39 | -92 | POLYGON ((-89.66292 36.02307, -90.31539 36.023... | 262,600,000,000 |
| 22 | District of Columbia | South | DC | 39 | -77 | POLYGON ((-77.04124 38.78954, -77.04123 38.789... | 185,200,000,000 |
| 23 | Wisconsin | Midwest | WI | 44 | -90 | POLYGON ((-91.2282 43.50125, -91.25466 43.6139... | 144,900,000,000 |
| 24 | Kentucky | South | KY | 37 | -86 | POLYGON ((-89.49836 36.5062, -89.27398 36.6115... | 136,600,000,000 |
| 25 | Arizona | West | AZ | 34 | -112 | POLYGON ((-109.04522 36.99991, -109.04367 31.3... | 125,000,000,000 |
| 26 | Maryland | South | MD | 39 | -77 | POLYGON ((-75.37754 38.01538, -75.37754 38.015... | 119,700,000,000 |
| 27 | Colorado | West | CO | 39 | -106 | POLYGON ((-102.05017 40.00081, -102.04012 38.4... | 117,000,000,000 |
| 28 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | 104,300,000,000 |
| 29 | Oregon | West | OR | 44 | -120 | POLYGON ((-116.915 45.99998, -116.679 45.80736... | 88,000,000,000 |
| 30 | Oklahoma | South | OK | 35 | -97 | POLYGON ((-103.00322 36.99516, -102.04118 36.9... | 48,100,000,000 |
| 31 | Nevada | West | NV | 39 | -117 | POLYGON ((-117.02825 42.00002, -114.03422 41.9... | 39,800,000,000 |
| 32 | Iowa | Midwest | IA | 42 | -93 | POLYGON ((-96.45266 43.50179, -95.35994 43.500... | 31,000,000,000 |
| 33 | Louisiana | South | LA | 31 | -92 | POLYGON ((-94.05976 33.01212, -93.09403 33.010... | 25,000,000,000 |
| 34 | Alabama | South | AL | 33 | -87 | POLYGON ((-88.16696 34.99967, -86.90968 34.999... | 16,800,000,000 |
| 35 | Delaware | South | DE | 39 | -75 | POLYGON ((-75.04839 38.44876, -75.71462 38.449... | 12,400,000,000 |
| 36 | Kansas | Midwest | KS | 38 | -98 | POLYGON ((-102.04118 36.99198, -102.04012 38.4... | 9,100,000,000 |
In [35]:
mtotrevco = gdfststotrevco.explore(column='Revenue (rounded)', name='Total Revenue of States', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mtotrevco)
mtotrevco
Out[35]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [36]:
# Average revenue in each State
dfstavrrev = df.groupby('State')[df.columns[[7]]].mean().sort_values('Revenue (rounded)', ascending=False)
dfstavrrev
Out[36]:
| Revenue (rounded) | |
|---|---|
| State | |
| Arkansas | 191,075,000,000 |
| Washington | 118,127,272,727 |
| Nebraska | 106,750,000,000 |
| Rhode Island | 88,060,000,000 |
| District of Columbia | 61,733,333,333 |
| Idaho | 52,150,000,000 |
| Texas | 49,644,444,444 |
| Minnesota | 47,211,764,706 |
| Kentucky | 45,533,333,333 |
| Oregon | 44,000,000,000 |
| North Carolina | 42,663,636,364 |
| California | 41,367,241,379 |
| Michigan | 40,160,000,000 |
| Indiana | 40,062,500,000 |
| Maryland | 39,900,000,000 |
| New York | 39,343,396,226 |
| Ohio | 36,992,857,143 |
| Connecticut | 35,473,333,333 |
| Pennsylvania | 35,389,473,684 |
| Missouri | 32,825,000,000 |
| Illinois | 32,506,250,000 |
| Georgia | 32,252,941,176 |
| Virginia | 29,536,000,000 |
| New Jersey | 29,393,333,333 |
| Tennessee | 28,427,272,727 |
| Massachusetts | 24,031,250,000 |
| Florida | 20,395,454,545 |
| Wisconsin | 18,112,500,000 |
| Oklahoma | 16,033,333,333 |
| Iowa | 15,500,000,000 |
| Colorado | 14,625,000,000 |
| Arizona | 13,888,888,889 |
| Nevada | 13,266,666,667 |
| Louisiana | 12,500,000,000 |
| Delaware | 12,400,000,000 |
| Kansas | 9,100,000,000 |
| Alabama | 8,400,000,000 |
In [37]:
# Draw the Map of the Average Revenue of Companies in each State
# Join the Dataframe 'gdfsts' with 'dfstavr'
gdfstsstavrrev = gdfsts.merge(dfstavrrev, how = 'inner', on = ['State'])
gdfstsstavrrev.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True).head(2)
Out[37]:
| State | region | postal | latitude | longitude | geometry | Revenue (rounded) | |
|---|---|---|---|---|---|---|---|
| 0 | Arkansas | South | AR | 35 | -92 | POLYGON ((-89.66292 36.02307, -89.67351 35.94,... | 191,075,000,000 |
| 1 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | 118,127,272,727 |
In [38]:
mstavrrev = gdfstsstavrrev.explore(column='Revenue (rounded)', name='Average Revenue of Companies in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstavrrev)
mstavrrev
Out[38]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [39]:
# Largest Employer Company in each State
dfmaxempco = df.head(1)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
mnmaxemp = dfst['Employees'].max()
dfstmaxempco = dfst.where(dfst['Employees'] == mnmaxemp).dropna()
dfmaxempco = pd.concat([dfmaxempco, dfstmaxempco], ignore_index=True)
dfmaxempco = dfmaxempco.drop(0)
#dfmaxempco['Employees'] = df['Employees'].astype(int)
dfmaxempco[['State','Company','Industry','City','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[39]:
| State | Company | Industry | City | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | Arkansas | Walmart | General Merchandisers | Bentonville | 72712 | 2,100,000 |
| 1 | Washington | Amazon | Internet Services and Retailing | Seattle | 98109 | 1,556,000 |
| 2 | Georgia | Home Depot | Specialty Retailers: Other | Atlanta | 30339 | 470,100 |
| 3 | California | Concentrix | Information Technology Services | Newark | 94560 | 450,000 |
| 4 | Minnesota | Target | General Merchandisers | Minneapolis | 55403 | 440,000 |
| 5 | Tennessee | FedEx | Mail, Package and Freight Delivery | Memphis | 38120 | 422,100 |
| 6 | Ohio | Kroger | Food & Drug Stores | Cincinnati | 45202 | 409,000 |
| 7 | Nebraska | Berkshire Hathaway | Insurance: Property and Casualty (Stock) | Omaha | 68131 | 392,400 |
| 8 | Massachusetts | TJX | Specialty Retailers: Apparel | Framingham | 01701 | 364,000 |
| 9 | New Jersey | Cognizant Technology | Information Technology Services | Teaneck | 07666 | 336,800 |
| 10 | New York | PepsiCo | Food Consumer Products | Purchase | 10577 | 319,000 |
| 11 | Pennsylvania | Aramark | Diversified Outsourcing Services | Philadelphia | 19103 | 266,700 |
| 12 | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | Woonsocket | 02895 | 259,500 |
| 13 | Florida | Publix Super Markets | Food & Drug Stores | Lakeland | 33811 | 255,000 |
| 14 | Illinois | Walgreens | Food & Drug Stores | Deerfield | 60015 | 252,500 |
| 15 | Texas | Yum China s | Food Services | Plano | 75074 | 245,500 |
| 16 | North Carolina | Lowe's | Specialty Retailers: Other | Mooresville | 28117 | 215,500 |
| 17 | Idaho | Albertsons | Food & Drug Stores | Boise | 83706 | 196,600 |
| 18 | Virginia | RTX | Aerospace & Defense | Arlington | 22209 | 186,000 |
| 19 | Michigan | Lear | Motor Vehicles & Parts | Southfield | 48033 | 173,700 |
| 20 | Maryland | Marriott International | Hotels, Casinos, Resorts | Bethesda | 20814 | 155,000 |
| 21 | Connecticut | GXO Logistics | Transportation and Logistics | Greenwich | 06831 | 128,500 |
| 22 | Indiana | Elevance Health | Health Care: Insurance and Managed Care | Indianapolis | 46204 | 103,700 |
| 23 | Missouri | O'Reilly Automotive | Specialty Retailers: Other | Springfield | 65802 | 85,600 |
| 24 | Oregon | Nike | Apparel | Beaverton | 97005 | 79,400 |
| 25 | Colorado | DaVita | Health Care: Medical Facilities | Denver | 80202 | 76,000 |
| 26 | Nevada | MGM Resorts International | Hotels, Casinos, Resorts | Las Vegas | 89109 | 69,000 |
| 27 | Kentucky | Humana | Health Care: Insurance and Managed Care | Louisville | 40202 | 65,700 |
| 28 | District of Columbia | Danaher | Medical Products and Equipment | Washington | 20037 | 62,000 |
| 29 | Wisconsin | Kohl's | General Merchandisers | Menomonee Falls | 53051 | 60,000 |
| 30 | Arizona | Republic Services | Waste Management | Phoenix | 85054 | 42,000 |
| 31 | Iowa | Casey's General Stores | Specialty Retailers: Other | Ankeny | 50021 | 33,100 |
| 32 | Louisiana | Lumen Technologies | Telecommunications | Monroe | 71203 | 25,000 |
| 33 | Delaware | DuPont | Chemicals | Wilmington | 19805 | 24,000 |
| 34 | Alabama | Regions Financial | Commercial Banks | Birmingham | 35203 | 19,600 |
| 35 | Kansas | Seaboard | Food Production | Merriam | 66202 | 14,000 |
| 36 | Oklahoma | Williams | Pipelines | Tulsa | 74172 | 5,800 |
In [40]:
# The Biggest Employer Company in each State.
# Join the Dataframe 'gdfsts' with 'dfmaxempco'
gdfstsmaxempco = gdfsts.merge(dfmaxempco, how = 'inner', on = ['State'])
gdfstsmaxempco.head(2)
Out[40]:
| State | region | postal | latitude | longitude | geometry | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Target | General Merchandisers | Minneapolis | 55403 | target.com | 440,000 | 106,600,000,000 | Brian Cornell |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | Albertsons | Food & Drug Stores | Boise | 83706 | albertsonscompanies.com | 196,600 | 79,200,000,000 | Susan Morris |
In [41]:
mmaxempco = gdfstsmaxempco.explore(column='Employees', name='Biggest Employer Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mmaxempco)
mmaxempco
Out[41]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [42]:
# Smallest Employer Company in each State
dfminempco = df.head(1)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
mnminemp = dfst['Employees'].min()
dfstminempco = dfst.where(dfst['Employees'] == mnminemp).dropna()
dfminempco = pd.concat([dfminempco, dfstminempco], ignore_index=True)
dfminempco = dfminempco.drop(0)
dfminempco[['State','Company','Industry','City','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[42]:
| State | Company | Industry | City | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | Idaho | Micron Technology | Semiconductors and Other Electronic Components | Boise | 83716 | 48,000 |
| 1 | Nevada | Las Vegas Sands | Hotels, Casinos, Resorts | Las Vegas | 89113 | 40,100 |
| 2 | Kentucky | Yum Brands | Food Services | Louisville | 40213 | 31,700 |
| 3 | Oregon | Lithia Motors | Automotive Retailing, Services | Medford | 97501 | 30,200 |
| 4 | Delaware | DuPont | Chemicals | Wilmington | 19805 | 24,000 |
| 5 | Iowa | Principal Financial | Insurance: Life, Health (Stock) | Des Moines | 50392 | 19,700 |
| 6 | Washington | Expedia | Internet Services and Retailing | Seattle | 98119 | 16,500 |
| 7 | Maryland | Constellation Energy | Energy | Baltimore | 21231 | 14,200 |
| 8 | Kansas | Seaboard | Food Production | Merriam | 66202 | 14,000 |
| 9 | Indiana | Steel Dynamics | Metals | Fort Wayne | 46804 | 13,000 |
| 10 | Louisiana | Entergy | Utilities: Gas and Electric | New Orleans | 70113 | 12,300 |
| 11 | Alabama | Vulcan Materials | Building Materials, Glass | Birmingham | 35242 | 12,000 |
| 12 | Arkansas | Murphy USA | Specialty Retailers: Other | El Dorado | 71730 | 11,600 |
| 13 | North Carolina | Sonic Automotive | Automotive Retailing, Services | Charlotte | 28211 | 10,800 |
| 14 | Illinois | Old Republic International | Insurance: Property and Casualty (Stock) | Chicago | 60601 | 9,400 |
| 15 | District of Columbia | Fannie Mae | Diversified Financials | Washington | 20005 | 8,200 |
| 16 | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | Lansing | 48917 | 7,300 |
| 17 | Wisconsin | WEC Energy | Utilities: Gas and Electric | Milwaukee | 53203 | 7,000 |
| 18 | Georgia | Pulte | Homebuilders | Atlanta | 30326 | 6,800 |
| 19 | Nebraska | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | Omaha | 68175 | 6,500 |
| 20 | Virginia | Altria | Tobacco | Richmond | 23230 | 6,200 |
| 21 | Rhode Island | FM | Insurance: Property and Casualty (Stock) | Johnston | 02919 | 5,800 |
| 22 | Pennsylvania | Toll Brothers | Homebuilders | Fort Washington | 19034 | 4,900 |
| 23 | Florida | World Kinect | Energy | Miami | 33178 | 4,700 |
| 24 | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | Chesterfield | 63017 | 4,100 |
| 25 | Minnesota | Thrivent Financial for Lutherans | Insurance: Life, Health (Mutual) | Minneapolis | 55415 | 4,000 |
| 26 | New Jersey | PBF Energy | Petroleum Refining | Parsippany | 07054 | 3,900 |
| 27 | Massachusetts | Global Partners | Energy | Waltham | 02453 | 3,800 |
| 28 | Connecticut | Interactive Brokers | Securities | Greenwich | 06830 | 3,000 |
| 29 | Arizona | Taylor Morrison Home | Homebuilders | Scottsdale | 85251 | 3,000 |
| 30 | Oklahoma | Devon Energy | Mining, Crude-Oil Production | Oklahoma City | 73102 | 2,300 |
| 31 | Tennessee | Delek US | Petroleum Refining | Brentwood | 37027 | 2,000 |
| 32 | New York | Hess | Mining, Crude-Oil Production | New York | 10036 | 1,800 |
| 33 | Texas | Cheniere Energy | Pipelines | Houston | 77002 | 1,700 |
| 34 | Colorado | Ovintiv | Mining, Crude-Oil Production | Denver | 80202 | 1,600 |
| 35 | Ohio | Welltower | Real Estate | Toledo | 43615 | 700 |
| 36 | California | A-Mark Precious Metals | Wholesalers: Diversified | El Segundo | 90245 | 500 |
In [43]:
# The Smallest Employer Company in each State.
# Join the Dataframe 'gdfsts' with 'dfminempco'
gdfstsminempco = gdfsts.merge(dfminempco, how = 'inner', on = ['State'])
gdfstsminempco.head(2)
Out[43]:
| State | region | postal | latitude | longitude | geometry | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Thrivent Financial for Lutherans | Insurance: Life, Health (Mutual) | Minneapolis | 55415 | thrivent.com | 4,000 | 10,900,000,000 | Teresa Rasmussen |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | Micron Technology | Semiconductors and Other Electronic Components | Boise | 83716 | micron.com | 48,000 | 25,100,000,000 | Sanjay Mehrotra |
In [44]:
mminempco = gdfstsminempco.explore(column='Employees', name='Smallest Employer Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mminempco)
mminempco
Out[44]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [155]:
# Check Total Employee in each State
dfstte = df.groupby('State').sum('Employees').sort_values('Employees', ascending=False)
dfstte
Out[155]:
| Employees | Revenue (rounded) | |
|---|---|---|
| State | ||
| California | 2857700 | 2,399,300,000,000 |
| New York | 2825500 | 2,085,200,000,000 |
| Washington | 2750600 | 1,299,400,000,000 |
| Texas | 2432800 | 2,680,800,000,000 |
| Arkansas | 2283200 | 764,300,000,000 |
| Illinois | 1655400 | 1,040,200,000,000 |
| Virginia | 1461200 | 738,400,000,000 |
| Georgia | 1327300 | 548,300,000,000 |
| Minnesota | 1269900 | 802,600,000,000 |
| Ohio | 1255100 | 1,035,800,000,000 |
| Tennessee | 1190500 | 312,700,000,000 |
| Florida | 1058700 | 448,700,000,000 |
| New Jersey | 944300 | 440,900,000,000 |
| Pennsylvania | 929200 | 672,400,000,000 |
| North Carolina | 856900 | 469,300,000,000 |
| Massachusetts | 854000 | 384,500,000,000 |
| Michigan | 838000 | 602,400,000,000 |
| Connecticut | 806700 | 532,100,000,000 |
| Nebraska | 463100 | 427,000,000,000 |
| Rhode Island | 344900 | 440,300,000,000 |
| Indiana | 336600 | 320,500,000,000 |
| Missouri | 305400 | 262,600,000,000 |
| Maryland | 290200 | 119,700,000,000 |
| Idaho | 244600 | 104,300,000,000 |
| Wisconsin | 196500 | 144,900,000,000 |
| Arizona | 194000 | 125,000,000,000 |
| Colorado | 194000 | 117,000,000,000 |
| Nevada | 159100 | 39,800,000,000 |
| Kentucky | 134400 | 136,600,000,000 |
| Oregon | 109600 | 88,000,000,000 |
| District of Columbia | 93200 | 185,200,000,000 |
| Iowa | 52800 | 31,000,000,000 |
| Louisiana | 37300 | 25,000,000,000 |
| Alabama | 31600 | 16,800,000,000 |
| Delaware | 24000 | 12,400,000,000 |
| Kansas | 14000 | 9,100,000,000 |
| Oklahoma | 13300 | 48,100,000,000 |
In [156]:
# Map of Total Employee in each State.
# Join the Dataframe 'gdfsts' with 'dfstte'
gdfstsstte = gdfsts.merge(dfstte, how = 'inner', on = ['State'])
gdfstsstte.head(2)
Out[156]:
| State | region | postal | latitude | longitude | geometry | Employees | Revenue (rounded) | |
|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | 1269900 | 802,600,000,000 |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | 244600 | 104,300,000,000 |
In [157]:
mstte = gdfstsstte.explore(column='Employees', name='Total Employee in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstte)
mstte
Out[157]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [48]:
# Check Average Number of Employee in each State
dfstavremp = df.groupby('State')[df.columns[[6]]].mean('Employees').sort_values('Employees', ascending=False)
dfstavremp
Out[48]:
| Employees | |
|---|---|
| State | |
| Arkansas | 570,800 |
| Washington | 250,055 |
| Idaho | 122,300 |
| Nebraska | 115,775 |
| Tennessee | 108,227 |
| Maryland | 96,733 |
| Georgia | 78,076 |
| North Carolina | 77,900 |
| Minnesota | 74,700 |
| Rhode Island | 68,980 |
| New Jersey | 62,953 |
| Virginia | 58,448 |
| Michigan | 55,867 |
| Oregon | 54,800 |
| Connecticut | 53,780 |
| Massachusetts | 53,375 |
| New York | 53,311 |
| Nevada | 53,033 |
| Illinois | 51,731 |
| California | 49,271 |
| Pennsylvania | 48,905 |
| Florida | 48,123 |
| Texas | 45,052 |
| Ohio | 44,825 |
| Kentucky | 44,800 |
| Indiana | 42,075 |
| Missouri | 38,175 |
| District of Columbia | 31,067 |
| Iowa | 26,400 |
| Wisconsin | 24,562 |
| Colorado | 24,250 |
| Delaware | 24,000 |
| Arizona | 21,556 |
| Louisiana | 18,650 |
| Alabama | 15,800 |
| Kansas | 14,000 |
| Oklahoma | 4,433 |
In [49]:
# The Average Number of Employee in each State.
# Join the Dataframe 'gdfsts' with 'dfstavremp'
gdfstsstavremp = gdfsts.merge(dfstavremp, how = 'inner', on = ['State'])
gdfstsstavremp.head(2)
Out[49]:
| State | region | postal | latitude | longitude | geometry | Employees | |
|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | 74,700 |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | 122,300 |
In [50]:
mstavremp = gdfstsstavremp.explore(column='Employees', name='Average Number of Employee in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstavremp)
mstavremp
Out[50]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [51]:
# Check the Most Efficient Company in each State
# Efficient here means how big Revenue is produced by each Employee.
dfstmaxeffco = df.head(1)
dfstmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
dfst[['Zip Code']] = int(dfst['Zip Code'].iloc[0])
dfstmaxeffco = pd.concat([dfstmaxeffco, dfst.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
dfstmaxeffco = dfstmaxeffco.drop(0)
dfstmaxeffco[['State','City','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[51]:
| State | City | Company | Industry | Zip Code | Efficiency | |
|---|---|---|---|---|---|---|
| 0 | New York | New York | StoneX | Diversified Financials | 10017 | 22,200,000 |
| 1 | California | El Segundo | A-Mark Precious Metals | Wholesalers: Diversified | 95014 | 19,400,000 |
| 2 | District of Columbia | Washington | Fannie Mae | Diversified Financials | 20005 | 18,621,951 |
| 3 | Virginia | McLean | Freddie Mac | Diversified Financials | 22102 | 15,074,074 |
| 4 | Texas | San Antonio | Valero Energy | Petroleum Refining | 77389 | 12,525,253 |
| 5 | Ohio | Toledo | Welltower | Real Estate | 43017 | 11,428,571 |
| 6 | Florida | Miami | World Kinect | Energy | 33811 | 8,978,723 |
| 7 | New Jersey | Parsippany | PBF Energy | Petroleum Refining | 8933 | 8,487,179 |
| 8 | Oklahoma | Oklahoma City | Devon Energy | Mining, Crude-Oil Production | 74103 | 6,913,043 |
| 9 | Pennsylvania | Conshohocken | Cencora | Wholesalers: Health Care | 19428 | 6,681,818 |
| 10 | Tennessee | Brentwood | Delek US | Petroleum Refining | 38120 | 6,250,000 |
| 11 | Colorado | Denver | Ovintiv | Mining, Crude-Oil Production | 80112 | 5,750,000 |
| 12 | Missouri | Chesterfield | Reinsurance of America | Insurance: Life, Health (Stock) | 63105 | 5,390,244 |
| 13 | Wisconsin | Milwaukee | Northwestern Mutual | Insurance: Life, Health (Mutual) | 53202 | 5,048,780 |
| 14 | Massachusetts | Waltham | Global Partners | Energy | 1701 | 4,526,316 |
| 15 | Minnesota | Inver Grove Heights | CHS | Food Production | 55344 | 3,672,897 |
| 16 | Connecticut | Bloomfield | Cigna | Health Care: Pharmacy and Other Services | 6002 | 3,412,983 |
| 17 | Arizona | Scottsdale | Taylor Morrison Home | Homebuilders | 85004 | 2,733,333 |
| 18 | Georgia | Atlanta | Pulte | Homebuilders | 30339 | 2,632,353 |
| 19 | Nebraska | Omaha | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | 68131 | 2,246,154 |
| 20 | Michigan | Lansing | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48265 | 2,164,384 |
| 21 | Illinois | Chicago | Archer Daniels Midland | Food Production | 60015 | 1,979,167 |
| 22 | Rhode Island | Johnston | FM | Insurance: Property and Casualty (Stock) | 2895 | 1,793,103 |
| 23 | Kentucky | Louisville | Humana | Health Care: Insurance and Managed Care | 40202 | 1,792,998 |
| 24 | Indiana | Indianapolis | Elevance Health | Health Care: Insurance and Managed Care | 46204 | 1,706,847 |
| 25 | Maryland | Baltimore | Constellation Energy | Energy | 20817 | 1,661,972 |
| 26 | Arkansas | El Dorado | Murphy USA | Specialty Retailers: Other | 72712 | 1,543,103 |
| 27 | North Carolina | Charlotte | Sonic Automotive | Automotive Retailing, Services | 28255 | 1,314,815 |
| 28 | Oregon | Medford | Lithia Motors | Automotive Retailing, Services | 97005 | 1,211,921 |
| 29 | Washington | Bellevue | Paccar | Motor Vehicles & Parts | 98109 | 1,119,601 |
| 30 | Louisiana | New Orleans | Entergy | Utilities: Gas and Electric | 71203 | 967,480 |
| 31 | Iowa | Des Moines | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 817,259 |
| 32 | Kansas | Merriam | Seaboard | Food Production | 66202 | 650,000 |
| 33 | Alabama | Birmingham | Vulcan Materials | Building Materials, Glass | 35203 | 616,667 |
| 34 | Idaho | Boise | Micron Technology | Semiconductors and Other Electronic Components | 83706 | 522,917 |
| 35 | Delaware | Wilmington | DuPont | Chemicals | 19805 | 516,667 |
| 36 | Nevada | Las Vegas | Las Vegas Sands | Hotels, Casinos, Resorts | 89109 | 281,796 |
In [52]:
# The Most Efficient Company in each State.
# Join the Dataframe 'gdfsts' with 'dfstmaxeffco'
gdfstsmaxeffco = gdfsts.merge(dfstmaxeffco, how = 'inner', on = ['State'])
gdfstsmaxeffco.head(2)
Out[52]:
| State | region | postal | latitude | longitude | geometry | Efficiency | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | 3,672,897 | CHS | Food Production | Inver Grove Heights | 55344 | chsinc.com | 10,700 | 39,300,000,000 | Jay Debertin |
| 1 | Idaho | West | ID | 44 | -114 | POLYGON ((-116.04823 49.00037, -115.9678 47.95... | 522,917 | Micron Technology | Semiconductors and Other Electronic Components | Boise | 83706 | micron.com | 48,000 | 25,100,000,000 | Sanjay Mehrotra |
In [53]:
mstmaxeffco = gdfstsmaxeffco.explore(column='Efficiency', name='Most Efficient Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstmaxeffco)
mstmaxeffco
Out[53]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [54]:
# Check the Least Efficient Company in each State
dfstmineffco = df.head(1)
dfstmineffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
dfstmineffco = pd.concat([dfstmineffco, dfst.sort_values(by='Efficiency',ascending=True).head(1)], ignore_index=True)
dfstmineffco = dfstmineffco.drop(0)
dfstmineffco[['State','City','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[54]:
| State | City | Company | Industry | Zip Code | Efficiency | |
|---|---|---|---|---|---|---|
| 0 | Oklahoma | Tulsa | Williams | Pipelines | 74172 | 1,810,345 |
| 1 | Kansas | Merriam | Seaboard | Food Production | 66202 | 650,000 |
| 2 | Oregon | Beaverton | Nike | Apparel | 97005 | 647,355 |
| 3 | Nebraska | Omaha | Peter Kiewit Sons' | Engineering & Construction | 68102 | 528,302 |
| 4 | Louisiana | Monroe | Lumen Technologies | Telecommunications | 71203 | 524,000 |
| 5 | Delaware | Wilmington | DuPont | Chemicals | 19805 | 516,667 |
| 6 | Alabama | Birmingham | Regions Financial | Commercial Banks | 35203 | 479,592 |
| 7 | Iowa | Ankeny | Casey's General Stores | Specialty Retailers: Other | 50021 | 450,151 |
| 8 | Rhode Island | Providence | Textron | Aerospace & Defense | 02903 | 402,941 |
| 9 | Idaho | Boise | Albertsons | Food & Drug Stores | 83706 | 402,848 |
| 10 | District of Columbia | Washington | Xylem | Industrial Machinery | 20003 | 373,913 |
| 11 | Arkansas | Bentonville | Walmart | General Merchandisers | 72712 | 324,286 |
| 12 | Indiana | Evansville | Berry Global | Packaging, Containers | 47710 | 292,857 |
| 13 | Wisconsin | Menomonee Falls | Kohl's | General Merchandisers | 53051 | 270,000 |
| 14 | Georgia | Atlanta | UPS | Mail, Package and Freight Delivery | 30328 | 244,761 |
| 15 | Minnesota | Minneapolis | Target | General Merchandisers | 55403 | 242,273 |
| 16 | Kentucky | Louisville | Yum Brands | Food Services | 40213 | 236,593 |
| 17 | Nevada | Reno | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 226,000 |
| 18 | Arizona | Phoenix | Sprouts Farmers Market | Food & Drug Stores | 85054 | 220,000 |
| 19 | Ohio | Cincinnati | Cintas | Diversified Outsourcing Services | 45262 | 206,452 |
| 20 | Missouri | Springfield | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 195,093 |
| 21 | Tennessee | Memphis | AutoZone | Specialty Retailers: Other | 38103 | 183,532 |
| 22 | North Carolina | Durham | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 175,000 |
| 23 | Illinois | Chicago | McDonald's | Food Services | 60607 | 172,667 |
| 24 | Colorado | Denver | DaVita | Health Care: Medical Facilities | 80202 | 168,421 |
| 25 | Maryland | Bethesda | Marriott International | Hotels, Casinos, Resorts | 20814 | 161,935 |
| 26 | Massachusetts | Framingham | TJX | Specialty Retailers: Apparel | 01701 | 154,945 |
| 27 | Michigan | Southfield | Lear | Motor Vehicles & Parts | 48033 | 134,139 |
| 28 | Washington | Seattle | Starbucks | Food Services | 98134 | 100,277 |
| 29 | Connecticut | Greenwich | GXO Logistics | Transportation and Logistics | 06831 | 91,051 |
| 30 | New York | New York | ABM Industries | Diversified Outsourcing Services | 10006 | 71,795 |
| 31 | Pennsylvania | Philadelphia | Aramark | Diversified Outsourcing Services | 19103 | 65,242 |
| 32 | Virginia | McLean | Hilton | Hotels, Casinos, Resorts | 22102 | 61,878 |
| 33 | Florida | Orlando | Darden Restaurants | Food Services | 32837 | 59,655 |
| 34 | New Jersey | Teaneck | Cognizant Technology | Information Technology Services | 07666 | 58,492 |
| 35 | Texas | Plano | Yum China s | Food Services | 75074 | 46,029 |
| 36 | California | Newark | Concentrix | Information Technology Services | 94560 | 21,333 |
In [55]:
# Join the Dataframe 'gdfsts' with 'dfstmineffco'
gdfstsmineffco = gdfsts.merge(dfstmineffco, how = 'inner', on = ['State']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfstsmineffco.head(2)
Out[55]:
| State | region | postal | latitude | longitude | geometry | Efficiency | Company | Industry | City | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Oklahoma | South | OK | 35 | -97 | POLYGON ((-103.00322 36.99516, -102.04118 36.9... | 1,810,345 | Williams | Pipelines | Tulsa | 74172 | williams.com | 5,800 | 10,500,000,000 | Alan Armstrong |
| 1 | Kansas | Midwest | KS | 38 | -98 | POLYGON ((-102.04118 36.99198, -102.04012 38.4... | 650,000 | Seaboard | Food Production | Merriam | 66202 | seaboardcorp.com | 14,000 | 9,100,000,000 | Robert Steer |
In [56]:
mstmineffco = gdfstsmineffco.explore(column='Efficiency', name='Least Efficient Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstmineffco)
mstmineffco
Out[56]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [57]:
# Check the Average Efficiency in each State
dfstavreff = df.head(1)
dfstavreff.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
#print(dfct.groupby(['State','City'], as_index=False).mean('Efficiency'))
dfstavreff = pd.concat([dfstavreff, dfst.groupby(['State'], as_index=False).mean('Efficiency')], ignore_index=True)[['State','Efficiency']]
dfstavreff = dfstavreff.drop(0)
dfstavreff.sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[57]:
| State | Efficiency | |
|---|---|---|
| 0 | District of Columbia | 6,460,449 |
| 1 | Oklahoma | 4,298,822 |
| 2 | Texas | 2,644,095 |
| 3 | Ohio | 1,818,979 |
| 4 | New York | 1,747,529 |
| 5 | Missouri | 1,495,312 |
| 6 | California | 1,459,801 |
| 7 | Colorado | 1,366,474 |
| 8 | Virginia | 1,332,278 |
| 9 | Wisconsin | 1,320,243 |
| 10 | Massachusetts | 1,273,417 |
| 11 | New Jersey | 1,182,423 |
| 12 | Nebraska | 1,116,963 |
| 13 | Pennsylvania | 1,115,642 |
| 14 | Florida | 1,107,382 |
| 15 | Rhode Island | 1,088,965 |
| 16 | Minnesota | 1,083,344 |
| 17 | Connecticut | 972,484 |
| 18 | Tennessee | 945,176 |
| 19 | Oregon | 929,638 |
| 20 | Arizona | 929,285 |
| 21 | Michigan | 862,969 |
| 22 | Indiana | 807,850 |
| 23 | Maryland | 803,561 |
| 24 | Kentucky | 778,332 |
| 25 | Louisiana | 745,740 |
| 26 | Georgia | 742,803 |
| 27 | Illinois | 731,582 |
| 28 | North Carolina | 654,844 |
| 29 | Arkansas | 653,435 |
| 30 | Kansas | 650,000 |
| 31 | Iowa | 633,705 |
| 32 | Washington | 561,945 |
| 33 | Alabama | 548,129 |
| 34 | Delaware | 516,667 |
| 35 | Idaho | 462,883 |
| 36 | Nevada | 252,357 |
In [58]:
# Join the Dataframe 'dfstavreff' with 'df'
gdfstsstavreff = gdfsts.merge(dfstavreff, how = 'inner', on = ['State'])
gdfstsstavreff = gdfstavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfstsstavreff
--------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[58], line 3 1 # Join the Dataframe 'dfstavreff' with 'df' 2 gdfstsstavreff = gdfsts.merge(dfstavreff, how = 'inner', on = ['State']) ----> 3 gdfstsstavreff = gdfstavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True) 4 gdfstsstavreff NameError: name 'gdfstavreff' is not defined
In [ ]:
mstavreff = gdfstsstavreff.explore(column='Efficiency', name='The Average Efficiency in each State', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstavreff)
mstavreff
In [ ]:
Statistics in City Level¶
In [158]:
# Grab all distinct City names
dfcts = df[['City','State']]
dfcts = dfcts.drop_duplicates()
dfcts = dfcts.sort_values('City', ascending=True).reset_index(drop=True)
ctslist = dfcts.to_numpy().tolist()
ctslist[1][0]
for cts in ctslist:
print(cts[0], ',', cts[1])
#print("---------------")
Abbott Park , Illinois Akron , Ohio Allentown , Pennsylvania Ankeny , Iowa Antioch , Tennessee Arden Hills , Minnesota Arlington , Virginia Arlington , Texas Armonk , New York Ashburn , Virginia Atlanta , Georgia Auburn Hills , Michigan Austin , Minnesota Austin , Texas Baltimore , Maryland Beaverton , Oregon Bellevue , Washington Benton Harbor , Michigan Bentonville , Arkansas Bethesda , Maryland Beverly Hills , California Birmingham , Alabama Bloomfield , Connecticut Bloomfield Hills , Michigan Bloomington , Illinois Boise , Idaho Bolingbrook , Illinois Boston , Massachusetts Brentwood , Tennessee Buffalo , New York Burbank , California Burlington , Massachusetts Burlington , New Jersey Burlington , North Carolina Byron Center , Michigan Calhoun , Georgia Cambridge , Massachusetts Camden , New Jersey Canonsburg , Pennsylvania Centennial , Colorado Chandler , Arizona Charlotte , North Carolina Chattanooga , Tennessee Chesapeake , Virginia Chesterfield , Missouri Chicago , Illinois Cincinnati , Ohio Cleveland , Ohio Columbus , Georgia Columbus , Indiana Columbus , Ohio Conshohocken , Pennsylvania Coral Gables , Florida Coraopolis , Pennsylvania Corning , New York Corona , California Cupertino , California Dallas , Texas Dearborn , Michigan Deerfield , Illinois Denver , Colorado Des Moines , Iowa Des Peres , Missouri Detroit , Michigan Downers Grove , Illinois Dublin , Ohio Dublin , California Duluth , Georgia Durham , North Carolina Eden Prairie , Minnesota El Dorado , Arkansas El Segundo , California Elkhart , Indiana Englewood , Colorado Erie , Pennsylvania Estero , Florida Evansville , Indiana Evendale , Ohio Fairfield , Ohio Falls Church , Virginia Farmington , Connecticut Findlay , Ohio Fort Lauderdale , Florida Fort Washington , Pennsylvania Fort Wayne , Indiana Fort Worth , Texas Foster City , California Framingham , Massachusetts Franklin , Tennessee Franklin Lakes , New Jersey Fremont , California Glen Allen , Virginia Glenview , Illinois Goodlettsville , Tennessee Greenwich , Connecticut Hartford , Connecticut Herndon , Virginia Hershey , Pennsylvania Houston , Texas Indianapolis , Indiana Inver Grove Heights , Minnesota Irvine , California Irving , Texas Issaquah , Washington Jackson , Michigan Jacksonville , Florida Johnston , Rhode Island Juno Beach , Florida King of Prussia , Pennsylvania Kingsport , Tennessee Lake Forest , Illinois Lakeland , Florida Lansing , Michigan Las Vegas , Nevada Livonia , Michigan Long Beach , California Long Island City , New York Los Gatos , California Louisville , Kentucky Lowell , Arkansas Madison , Wisconsin Manhattan Beach , California Maplewood , Minnesota Marlborough , Massachusetts Maumee , Ohio Mayfield Village , Ohio McLean , Virginia Medford , Oregon Melbourne , Florida Melville , New York Memphis , Tennessee Menlo Park , California Menomonee Falls , Wisconsin Mentor , Ohio Merriam , Kansas Miami , Florida Midland , Texas Midland , Michigan Milpitas , California Milwaukee , Wisconsin Minneapolis , Minnesota Moline , Illinois Monroe , Louisiana Mooresville , North Carolina Mountain View , California Nashville , Tennessee New Braunfels , Texas New Britain , Connecticut New Brunswick , New Jersey New Orleans , Louisiana New York , New York Newark , California Newark , New Jersey Newport Beach , California Newport News , Virginia North Chicago , Illinois Northbrook , Illinois Norwalk , Connecticut Oak Brook , Illinois Oakland , California Oklahoma City , Oklahoma Omaha , Nebraska Orlando , Florida Orrville , Ohio Oshkosh , Wisconsin Palm Beach Gardens , Florida Palo Alto , California Parsippany , New Jersey Philadelphia , Pennsylvania Phoenix , Arizona Pittsburgh , Pennsylvania Plano , Texas Plantation , Florida Pleasanton , California Portage , Michigan Princeton , New Jersey Providence , Rhode Island Purchase , New York Radnor , Pennsylvania Rahway , New Jersey Raleigh , North Carolina Redmond , Washington Redwood City , California Reno , Nevada Reston , Virginia Richfield , Minnesota Richmond , Virginia Riverwoods , Illinois Rolling Meadows , Illinois Roseland , New Jersey Rosemead , California Rosemont , Illinois Round Rock , Texas San Antonio , Texas San Diego , California San Francisco , California San Jose , California San Mateo , California Santa Clara , California Scottsdale , Arizona Seattle , Washington Secaucus , New Jersey Southfield , Michigan Spring , Texas Springdale , Arkansas Springfield , Massachusetts Springfield , Missouri St. Louis , Missouri St. Paul , Minnesota St. Petersburg , Florida Stamford , Connecticut Summit , New Jersey Sumner , Washington Sunny Isles Beach , Florida Sunnyvale , California Tampa , Florida Tarrytown , New York Teaneck , New Jersey Tempe , Arizona Thousand Oaks , California Toledo , Ohio Tulsa , Oklahoma Vernon Hills , Illinois Victor , New York Wallingford , Connecticut Waltham , Massachusetts Warsaw , Indiana Washington , District of Columbia Westchester , Illinois Westerville , Ohio Westlake , Texas Westminster , Colorado Wilmington , Delaware Wilmington , Massachusetts Winona , Minnesota Woodland Hills , California Woonsocket , Rhode Island
In [159]:
df.where(df['Zip Code'] == '44143').dropna()
Out[159]:
| Company | Industry | City | State | Zip Code | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|
| 56 | Progressive | Insurance: Property and Casualty (Stock) | Mayfield Village | Ohio | 44143 | progressive.com | 66,300 | 75,400,000,000 | Susan Patricia Griffith |
In [160]:
# Check the Largest Revenue Company in each City
dfmaxrevco = df.head(1)
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
mnmaxrev = dfct['Revenue (rounded)'].max()
dfctmaxrevco = dfct.where(dfct['Revenue (rounded)'] == mnmaxrev).dropna()
dfmaxrevco = pd.concat([dfmaxrevco, dfctmaxrevco], ignore_index=True)
dfmaxrevco = dfmaxrevco.drop(0)
dfmaxrevco[['City','State','Company','Industry','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[160]:
| City | State | Company | Industry | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 681,000,000,000 |
| 1 | Seattle | Washington | Amazon | Internet Services and Retailing | 98109 | 638,000,000,000 |
| 2 | Eden Prairie | Minnesota | UnitedHealth | Health Care: Insurance and Managed Care | 55344 | 400,300,000,000 |
| 3 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 391,000,000,000 |
| 4 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 372,800,000,000 |
| 5 | Omaha | Nebraska | Berkshire Hathaway | Insurance: Property and Casualty (Stock) | 68131 | 371,400,000,000 |
| 6 | Mountain View | California | Alphabet | Internet Services and Retailing | 94043 | 350,000,000,000 |
| 7 | Spring | Texas | Exxon Mobil | Petroleum Refining | 77389 | 349,600,000,000 |
| 8 | Irving | Texas | McKesson | Wholesalers: Health Care | 75039 | 309,000,000,000 |
| 9 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 294,000,000,000 |
| 10 | New York | New York | JPMorgan Chase | Commercial Banks | 10017 | 278,900,000,000 |
| 11 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 254,500,000,000 |
| 12 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 247,100,000,000 |
| 13 | Redmond | Washington | Microsoft | Computer Software | 98052 | 245,100,000,000 |
| 14 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 226,800,000,000 |
| 15 | Houston | Texas | Chevron | Petroleum Refining | 77002 | 202,800,000,000 |
| 16 | Charlotte | North Carolina | Bank of America | Commercial Banks | 28255 | 192,400,000,000 |
| 17 | Detroit | Michigan | General Motors | Motor Vehicles & Parts | 48265 | 187,400,000,000 |
| 18 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 185,000,000,000 |
| 19 | Indianapolis | Indiana | Elevance Health | Health Care: Insurance and Managed Care | 46204 | 177,000,000,000 |
| 20 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 164,500,000,000 |
| 21 | St. Louis | Missouri | Centene | Health Care: Insurance and Managed Care | 63105 | 163,100,000,000 |
| 22 | Atlanta | Georgia | Home Depot | Specialty Retailers: Other | 30339 | 159,500,000,000 |
| 23 | Washington | District of Columbia | Fannie Mae | Diversified Financials | 20005 | 152,700,000,000 |
| 24 | Deerfield | Illinois | Walgreens | Food & Drug Stores | 60015 | 147,700,000,000 |
| 25 | Cincinnati | Ohio | Kroger | Food & Drug Stores | 45202 | 147,100,000,000 |
| 26 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 140,400,000,000 |
| 27 | Santa Clara | California | Nvidia | Semiconductors and Other Electronic Components | 95051 | 130,500,000,000 |
| 28 | San Francisco | California | Wells Fargo | Commercial Banks | 94104 | 125,400,000,000 |
| 29 | San Antonio | Texas | Valero Energy | Petroleum Refining | 78249 | 124,000,000,000 |
| 30 | Philadelphia | Pennsylvania | Comcast | Telecommunications | 19103 | 123,700,000,000 |
| 31 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 123,000,000,000 |
| 32 | Dallas | Texas | AT&T | Telecommunications | 75202 | 122,300,000,000 |
| 33 | McLean | Virginia | Freddie Mac | Diversified Financials | 22102 | 122,100,000,000 |
| 34 | Louisville | Kentucky | Humana | Health Care: Insurance and Managed Care | 40202 | 117,800,000,000 |
| 35 | Minneapolis | Minnesota | Target | General Merchandisers | 55403 | 106,600,000,000 |
| 36 | Austin | Texas | Tesla | Motor Vehicles & Parts | 78725 | 97,700,000,000 |
| 37 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 95,600,000,000 |
| 38 | Purchase | New York | PepsiCo | Food Consumer Products | 10577 | 91,900,000,000 |
| 39 | Burbank | California | Walt Disney | Entertainment | 91521 | 91,400,000,000 |
| 40 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 88,800,000,000 |
| 41 | Memphis | Tennessee | FedEx | Mail, Package and Freight Delivery | 38120 | 87,700,000,000 |
| 42 | Chicago | Illinois | Archer Daniels Midland | Food Production | 60601 | 85,500,000,000 |
| 43 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 83,700,000,000 |
| 44 | Arlington | Virginia | RTX | Aerospace & Defense | 22209 | 80,700,000,000 |
| 45 | Boise | Idaho | Albertsons | Food & Drug Stores | 83706 | 79,200,000,000 |
| 46 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 75,400,000,000 |
| 47 | Bethesda | Maryland | Lockheed Martin | Aerospace & Defense | 20817 | 71,000,000,000 |
| 48 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 70,600,000,000 |
| 49 | Newark | New Jersey | Prudential Financial | Insurance: Life, Health (Stock) | 07102 | 70,400,000,000 |
| 50 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 64,200,000,000 |
| 51 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 64,100,000,000 |
| 52 | Armonk | New York | IBM | Information Technology Services | 10504 | 62,800,000,000 |
| 53 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 60,200,000,000 |
| 54 | Columbus | Ohio | Nationwide | Insurance: Property and Casualty (Mutual) | 43215 | 58,600,000,000 |
| 55 | Fremont | California | TD Synnex | Wholesalers: Electronics and Office Equipment | 94538 | 58,500,000,000 |
| 56 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 56,400,000,000 |
| 57 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 56,300,000,000 |
| 58 | Stamford | Connecticut | Charter Communications | Telecommunications | 06902 | 55,100,000,000 |
| 59 | Richmond | Virginia | Performance Food | Wholesalers: Food and Grocery | 23238 | 54,700,000,000 |
| 60 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 54,200,000,000 |
| 61 | San Jose | California | Cisco Systems | Network and Other Communications Equipment | 95134 | 53,800,000,000 |
| 62 | Palo Alto | California | HP | Computers, Office Equipment | 94304 | 53,600,000,000 |
| 63 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 53,300,000,000 |
| 64 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 51,700,000,000 |
| 65 | Beaverton | Oregon | Nike | Apparel | 97005 | 51,400,000,000 |
| 66 | Boston | Massachusetts | Liberty Mutual Insurance | Insurance: Property and Casualty (Stock) | 02116 | 50,400,000,000 |
| 67 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 48,300,000,000 |
| 68 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 48,000,000,000 |
| 69 | Reston | Virginia | General Dynamics | Aerospace & Defense | 20190 | 47,700,000,000 |
| 70 | Springfield | Massachusetts | Mass Mutual | Insurance: Life, Health (Mutual) | 01111 | 43,100,000,000 |
| 71 | Midland | Michigan | Dow | Chemicals | 48674 | 43,000,000,000 |
| 72 | Waltham | Massachusetts | Thermo Fisher Scientific | Scientific, Photographic and Control Equipment | 02451 | 42,900,000,000 |
| 73 | Miami | Florida | World Kinect | Energy | 33178 | 42,200,000,000 |
| 74 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 42,000,000,000 |
| 75 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 41,500,000,000 |
| 76 | Milwaukee | Wisconsin | Northwestern Mutual | Insurance: Life, Health (Mutual) | 53202 | 41,400,000,000 |
| 77 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 41,000,000,000 |
| 78 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 40,600,000,000 |
| 79 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 40,600,000,000 |
| 80 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 39,300,000,000 |
| 81 | Los Gatos | California | Netflix | Entertainment | 95032 | 39,000,000,000 |
| 82 | San Diego | California | Qualcomm | Semiconductors and Other Electronic Components | 92121 | 39,000,000,000 |
| 83 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 38,700,000,000 |
| 84 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 37,900,000,000 |
| 85 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 36,800,000,000 |
| 86 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 36,600,000,000 |
| 87 | Cambridge | Massachusetts | GE Vernova | Energy | 02141 | 34,900,000,000 |
| 88 | Pittsburgh | Pennsylvania | PNC | Commercial Banks | 15222 | 34,400,000,000 |
| 89 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 34,100,000,000 |
| 90 | Bellevue | Washington | Paccar | Motor Vehicles & Parts | 98004 | 33,700,000,000 |
| 91 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 33,400,000,000 |
| 92 | Parsippany | New Jersey | PBF Energy | Petroleum Refining | 07054 | 33,100,000,000 |
| 93 | Jacksonville | Florida | GuideWell Mutual | Insurance: Life, Health (Stock) | 32246 | 33,000,000,000 |
| 94 | Providence | Rhode Island | United Natural Foods | Wholesalers: Food and Grocery | 02908 | 31,000,000,000 |
| 95 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 30,800,000,000 |
| 96 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 30,500,000,000 |
| 97 | Newport News | Virginia | Ferguson | Wholesalers: Diversified | 23606 | 29,600,000,000 |
| 98 | St. Petersburg | Florida | Jabil | Semiconductors and Other Electronic Components | 33716 | 28,900,000,000 |
| 99 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 28,800,000,000 |
| 100 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 27,900,000,000 |
| 101 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 26,800,000,000 |
| 102 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 26,500,000,000 |
| 103 | Westlake | Texas | Charles Schwab | Securities | 76262 | 26,000,000,000 |
| 104 | Phoenix | Arizona | Freeport-McMoRan | Mining, Crude-Oil Production | 85004 | 25,500,000,000 |
| 105 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 24,800,000,000 |
| 106 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 24,800,000,000 |
| 107 | St. Paul | Minnesota | 3M | Chemicals | 55144 | 24,600,000,000 |
| 108 | Oakland | California | PG&E | Utilities: Gas and Electric | 94612 | 24,400,000,000 |
| 109 | Norwalk | Connecticut | Booking s | Internet Services and Retailing | 06854 | 23,700,000,000 |
| 110 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 23,600,000,000 |
| 111 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 23,600,000,000 |
| 112 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 23,300,000,000 |
| 113 | Beverly Hills | California | Live Nation Entertainment | Entertainment | 90210 | 23,200,000,000 |
| 114 | Cleveland | Ohio | Sherwin-Williams | Chemicals | 44115 | 23,100,000,000 |
| 115 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 22,600,000,000 |
| 116 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 22,100,000,000 |
| 117 | Tulsa | Oklahoma | Oneok | Pipelines | 74103 | 21,700,000,000 |
| 118 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 21,300,000,000 |
| 119 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 21,300,000,000 |
| 120 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 21,100,000,000 |
| 121 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 21,000,000,000 |
| 122 | Marlborough | Massachusetts | BJ's Wholesale Club | General Merchandisers | 01752 | 20,500,000,000 |
| 123 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 20,200,000,000 |
| 124 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 19,700,000,000 |
| 125 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 19,200,000,000 |
| 126 | Akron | Ohio | Goodyear Tire & Rubber | Motor Vehicles & Parts | 44316 | 18,900,000,000 |
| 127 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 18,900,000,000 |
| 128 | Denver | Colorado | Newmont | Mining, Crude-Oil Production | 80237 | 18,700,000,000 |
| 129 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 18,400,000,000 |
| 130 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 17,900,000,000 |
| 131 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 17,600,000,000 |
| 132 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 17,500,000,000 |
| 133 | Las Vegas | Nevada | MGM Resorts International | Hotels, Casinos, Resorts | 89109 | 17,200,000,000 |
| 134 | Lake Forest | Illinois | W.W. Grainger | Wholesalers: Diversified | 60045 | 17,200,000,000 |
| 135 | Duluth | Georgia | Asbury Automotive | Automotive Retailing, Services | 30097 | 17,200,000,000 |
| 136 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 16,700,000,000 |
| 137 | Glen Allen | Virginia | Markel | Insurance: Property and Casualty (Stock) | 23060 | 16,600,000,000 |
| 138 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 16,600,000,000 |
| 139 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 16,300,000,000 |
| 140 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 16,200,000,000 |
| 141 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 16,200,000,000 |
| 142 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 16,100,000,000 |
| 143 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 15,900,000,000 |
| 144 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 15,900,000,000 |
| 145 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 15,800,000,000 |
| 146 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 15,800,000,000 |
| 147 | Englewood | Colorado | EchoStar | Telecommunications | 80112 | 15,800,000,000 |
| 148 | Newport Beach | California | Pacific Life | Insurance: Life, Health (Stock) | 92660 | 15,800,000,000 |
| 149 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 15,500,000,000 |
| 150 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 15,500,000,000 |
| 151 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 15,400,000,000 |
| 152 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 15,400,000,000 |
| 153 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 15,400,000,000 |
| 154 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 15,200,000,000 |
| 155 | Raleigh | North Carolina | First Citizens BancShares | Commercial Banks | 27609 | 15,000,000,000 |
| 156 | Brentwood | Tennessee | Tractor Supply | Specialty Retailers: Other | 37027 | 14,900,000,000 |
| 157 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 14,900,000,000 |
| 158 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 14,700,000,000 |
| 159 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 14,400,000,000 |
| 160 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 14,300,000,000 |
| 161 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 14,200,000,000 |
| 162 | Auburn Hills | Michigan | BorgWarner | Motor Vehicles & Parts | 48326 | 14,100,000,000 |
| 163 | Scottsdale | Arizona | Reliance | Metals | 85254 | 13,800,000,000 |
| 164 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 13,700,000,000 |
| 165 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 13,700,000,000 |
| 166 | Greenwich | Connecticut | W.R. Berkley | Insurance: Property and Casualty (Stock) | 06830 | 13,600,000,000 |
| 167 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 13,500,000,000 |
| 168 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 13,400,000,000 |
| 169 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 13,200,000,000 |
| 170 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 13,100,000,000 |
| 171 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 13,100,000,000 |
| 172 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 13,000,000,000 |
| 173 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 12,900,000,000 |
| 174 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 12,700,000,000 |
| 175 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 12,600,000,000 |
| 176 | Coral Gables | Florida | Ryder System | Transportation and Logistics | 33134 | 12,600,000,000 |
| 177 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 12,400,000,000 |
| 178 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 12,300,000,000 |
| 179 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 12,100,000,000 |
| 180 | Allentown | Pennsylvania | Air Products & Chemicals | Chemicals | 18106 | 12,100,000,000 |
| 181 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 12,100,000,000 |
| 182 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 11,900,000,000 |
| 183 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 11,900,000,000 |
| 184 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 11,900,000,000 |
| 185 | Tampa | Florida | Crown s | Packaging, Containers | 33637 | 11,800,000,000 |
| 186 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 11,600,000,000 |
| 187 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 11,400,000,000 |
| 188 | Maumee | Ohio | Andersons | Food Production | 43537 | 11,300,000,000 |
| 189 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 11,300,000,000 |
| 190 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 11,300,000,000 |
| 191 | Plano | Texas | Yum China s | Food Services | 75074 | 11,300,000,000 |
| 192 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 11,300,000,000 |
| 193 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 11,200,000,000 |
| 194 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 11,100,000,000 |
| 195 | Toledo | Ohio | Owens Corning | Building Materials, Glass | 43659 | 11,000,000,000 |
| 196 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 10,800,000,000 |
| 197 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 10,800,000,000 |
| 198 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 10,700,000,000 |
| 199 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 10,600,000,000 |
| 200 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 10,600,000,000 |
| 201 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 10,400,000,000 |
| 202 | Victor | New York | Constellation Brands | Beverages | 14564 | 10,000,000,000 |
| 203 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 10,000,000,000 |
| 204 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 10,000,000,000 |
| 205 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 9,900,000,000 |
| 206 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 9,800,000,000 |
| 207 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 9,800,000,000 |
| 208 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 9,700,000,000 |
| 209 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 9,600,000,000 |
| 210 | Newark | California | Concentrix | Information Technology Services | 94560 | 9,600,000,000 |
| 211 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 9,500,000,000 |
| 212 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 9,500,000,000 |
| 213 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 9,400,000,000 |
| 214 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 9,400,000,000 |
| 215 | Birmingham | Alabama | Regions Financial | Commercial Banks | 35203 | 9,400,000,000 |
| 216 | Long Island City | New York | JetBlue Airways | Airlines | 11101 | 9,300,000,000 |
| 217 | Merriam | Kansas | Seaboard | Food Production | 66202 | 9,100,000,000 |
| 218 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 9,000,000,000 |
| 219 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 9,000,000,000 |
| 220 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 8,800,000,000 |
| 221 | Chandler | Arizona | Insight Enterprises | Information Technology Services | 85286 | 8,700,000,000 |
| 222 | Redwood City | California | Equinix | Real Estate | 94065 | 8,700,000,000 |
| 223 | San Mateo | California | Franklin Resources | Securities | 94403 | 8,500,000,000 |
| 224 | Pleasanton | California | Workday | Computer Software | 94588 | 8,400,000,000 |
| 225 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 8,400,000,000 |
| 226 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 8,400,000,000 |
| 227 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 8,300,000,000 |
| 228 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 8,200,000,000 |
| 229 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 8,000,000,000 |
| 230 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 7,800,000,000 |
| 231 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 7,800,000,000 |
| 232 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 7,700,000,000 |
| 233 | Corona | California | Monster Beverage | Beverages | 92879 | 7,500,000,000 |
| 234 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 7,500,000,000 |
| 235 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 7,500,000,000 |
| 236 | Westchester | Illinois | Ingredion | Food Production | 60154 | 7,400,000,000 |
In [161]:
# Join the Dataframe 'gdfusact' with 'dfmaxrevco' for the Top 10
gdfusactmaxrevco = gdfusact.merge(dfmaxrevco, how = 'inner', on = ['Zip Code'])
gdfusactmaxrevco = gdfusactmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [162]:
mctmaxrevco = gdfusactmaxrevco.explore(column='Revenue (rounded)', name='Biggest Revenue Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxrevco)
mctmaxrevco
Out[162]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [163]:
# Check the Smallest Revenue Company in each City
dfminrevco = df.head(1)
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
mnminrev = dfct['Revenue (rounded)'].min()
dfctminrevco = dfct.where(dfct['Revenue (rounded)'] == mnminrev).dropna()
dfminrevco = pd.concat([dfminrevco, dfctminrevco], ignore_index=True)
dfminrevco = dfminrevco.drop(0)
dfminrevco[['City','State','Company','Industry','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[163]:
| City | State | Company | Industry | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 681,000,000,000 |
| 1 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 391,000,000,000 |
| 2 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 372,800,000,000 |
| 3 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 294,000,000,000 |
| 4 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 254,500,000,000 |
| 5 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 247,100,000,000 |
| 6 | Redmond | Washington | Microsoft | Computer Software | 98052 | 245,100,000,000 |
| 7 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 226,800,000,000 |
| 8 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 185,000,000,000 |
| 9 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 164,500,000,000 |
| 10 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 140,400,000,000 |
| 11 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 123,000,000,000 |
| 12 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 95,600,000,000 |
| 13 | Burbank | California | Walt Disney | Entertainment | 91521 | 91,400,000,000 |
| 14 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 88,800,000,000 |
| 15 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 83,700,000,000 |
| 16 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 75,400,000,000 |
| 17 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 70,600,000,000 |
| 18 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 64,200,000,000 |
| 19 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 64,100,000,000 |
| 20 | Armonk | New York | IBM | Information Technology Services | 10504 | 62,800,000,000 |
| 21 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 60,200,000,000 |
| 22 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 56,400,000,000 |
| 23 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 56,300,000,000 |
| 24 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 54,200,000,000 |
| 25 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 53,300,000,000 |
| 26 | Austin | Texas | Oracle | Computer Software | 78741 | 53,000,000,000 |
| 27 | Palo Alto | California | Broadcom | Semiconductors and Other Electronic Components | 94304 | 52,400,000,000 |
| 28 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 51,700,000,000 |
| 29 | Beaverton | Oregon | Nike | Apparel | 97005 | 51,400,000,000 |
| 30 | San Antonio | Texas | USAA | Insurance: Property and Casualty (Stock) | 78288 | 48,600,000,000 |
| 31 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 48,300,000,000 |
| 32 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 48,000,000,000 |
| 33 | Midland | Michigan | Dow | Chemicals | 48674 | 43,000,000,000 |
| 34 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 42,000,000,000 |
| 35 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 41,500,000,000 |
| 36 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 41,000,000,000 |
| 37 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 40,600,000,000 |
| 38 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 40,600,000,000 |
| 39 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 39,300,000,000 |
| 40 | Los Gatos | California | Netflix | Entertainment | 95032 | 39,000,000,000 |
| 41 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 38,700,000,000 |
| 42 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 37,900,000,000 |
| 43 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 36,800,000,000 |
| 44 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 36,600,000,000 |
| 45 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 34,100,000,000 |
| 46 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 33,400,000,000 |
| 47 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 30,800,000,000 |
| 48 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 30,500,000,000 |
| 49 | Spring | Texas | Hewlett Packard | Computers, Office Equipment | 77389 | 30,100,000,000 |
| 50 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 28,800,000,000 |
| 51 | Purchase | New York | Mastercard | Financial Data Services | 10577 | 28,200,000,000 |
| 52 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 27,900,000,000 |
| 53 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 26,800,000,000 |
| 54 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 26,500,000,000 |
| 55 | Westlake | Texas | Charles Schwab | Securities | 76262 | 26,000,000,000 |
| 56 | Boise | Idaho | Micron Technology | Semiconductors and Other Electronic Components | 83716 | 25,100,000,000 |
| 57 | Bethesda | Maryland | Marriott International | Hotels, Casinos, Resorts | 20814 | 25,100,000,000 |
| 58 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 24,800,000,000 |
| 59 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 24,800,000,000 |
| 60 | Oakland | California | Block | Financial Data Services | 94612 | 24,100,000,000 |
| 61 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 23,600,000,000 |
| 62 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 23,600,000,000 |
| 63 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 23,300,000,000 |
| 64 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 22,600,000,000 |
| 65 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 22,100,000,000 |
| 66 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 21,300,000,000 |
| 67 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 21,300,000,000 |
| 68 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 21,100,000,000 |
| 69 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 21,000,000,000 |
| 70 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 20,200,000,000 |
| 71 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 19,700,000,000 |
| 72 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 19,200,000,000 |
| 73 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 18,900,000,000 |
| 74 | Memphis | Tennessee | AutoZone | Specialty Retailers: Other | 38103 | 18,500,000,000 |
| 75 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 18,400,000,000 |
| 76 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 17,900,000,000 |
| 77 | Eden Prairie | Minnesota | C.H. Robinson Worldwide | Transportation and Logistics | 55347 | 17,700,000,000 |
| 78 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 17,600,000,000 |
| 79 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 17,500,000,000 |
| 80 | Philadelphia | Pennsylvania | Aramark | Diversified Outsourcing Services | 19103 | 17,400,000,000 |
| 81 | Waltham | Massachusetts | Global Partners | Energy | 02453 | 17,200,000,000 |
| 82 | Indianapolis | Indiana | Corteva | Food Production | 46268 | 16,900,000,000 |
| 83 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 16,700,000,000 |
| 84 | Marlborough | Massachusetts | Boston Scientific | Medical Products and Equipment | 01752 | 16,700,000,000 |
| 85 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 16,600,000,000 |
| 86 | Mountain View | California | Intuit | Computer Software | 94043 | 16,300,000,000 |
| 87 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 16,300,000,000 |
| 88 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 16,200,000,000 |
| 89 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 16,200,000,000 |
| 90 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 16,100,000,000 |
| 91 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 15,900,000,000 |
| 92 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 15,900,000,000 |
| 93 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 15,800,000,000 |
| 94 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 15,800,000,000 |
| 95 | Dallas | Texas | Texas Instruments | Semiconductors and Other Electronic Components | 75243 | 15,600,000,000 |
| 96 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 15,500,000,000 |
| 97 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 15,500,000,000 |
| 98 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 15,400,000,000 |
| 99 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 15,400,000,000 |
| 100 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 15,400,000,000 |
| 101 | Stamford | Connecticut | United Rentals | Specialty Retailers: Other | 06902 | 15,300,000,000 |
| 102 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 15,200,000,000 |
| 103 | Deerfield | Illinois | Baxter International | Medical Products and Equipment | 60015 | 15,100,000,000 |
| 104 | St. Petersburg | Florida | Raymond James Financial | Securities | 33716 | 14,900,000,000 |
| 105 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 14,900,000,000 |
| 106 | Fremont | California | Lam Research | Semiconductors and Other Electronic Components | 94538 | 14,900,000,000 |
| 107 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 14,700,000,000 |
| 108 | Norwalk | Connecticut | EMCOR | Engineering & Construction | 06851 | 14,600,000,000 |
| 109 | Omaha | Nebraska | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | 68175 | 14,600,000,000 |
| 110 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 14,400,000,000 |
| 111 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 14,300,000,000 |
| 112 | Charlotte | North Carolina | Sonic Automotive | Automotive Retailing, Services | 28211 | 14,200,000,000 |
| 113 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 14,200,000,000 |
| 114 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 13,700,000,000 |
| 115 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 13,700,000,000 |
| 116 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 13,500,000,000 |
| 117 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 13,400,000,000 |
| 118 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 13,200,000,000 |
| 119 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 13,100,000,000 |
| 120 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 13,100,000,000 |
| 121 | Akron | Ohio | FirstEnergy | Utilities: Gas and Electric | 44308 | 13,000,000,000 |
| 122 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 13,000,000,000 |
| 123 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 12,900,000,000 |
| 124 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 12,700,000,000 |
| 125 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 12,600,000,000 |
| 126 | Brentwood | Tennessee | Delek US | Petroleum Refining | 37027 | 12,500,000,000 |
| 127 | Detroit | Michigan | DTE Energy | Utilities: Gas and Electric | 48226 | 12,500,000,000 |
| 128 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 12,400,000,000 |
| 129 | Providence | Rhode Island | Citizens Financial | Commercial Banks | 02903 | 12,400,000,000 |
| 130 | San Diego | California | LPL Financial s | Securities | 92121 | 12,400,000,000 |
| 131 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 12,300,000,000 |
| 132 | Arlington | Virginia | AES | Utilities: Gas and Electric | 22203 | 12,300,000,000 |
| 133 | Coral Gables | Florida | MasTec | Engineering & Construction | 33134 | 12,300,000,000 |
| 134 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 12,100,000,000 |
| 135 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 12,100,000,000 |
| 136 | Columbus | Ohio | Huntington Bancshares | Commercial Banks | 43287 | 12,000,000,000 |
| 137 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 11,900,000,000 |
| 138 | Springfield | Massachusetts | Eversource Energy | Utilities: Gas and Electric | 01104 | 11,900,000,000 |
| 139 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 11,900,000,000 |
| 140 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 11,900,000,000 |
| 141 | Seattle | Washington | Alaska Air | Airlines | 98188 | 11,700,000,000 |
| 142 | Duluth | Georgia | AGCO | Construction and Farm Machinery | 30096 | 11,700,000,000 |
| 143 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 11,600,000,000 |
| 144 | Newport News | Virginia | Huntington Ingalls Industries | Aerospace & Defense | 23607 | 11,500,000,000 |
| 145 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 11,400,000,000 |
| 146 | Newport Beach | California | Chipotle Mexican Grill | Food Services | 92660 | 11,300,000,000 |
| 147 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 11,300,000,000 |
| 148 | Las Vegas | Nevada | Las Vegas Sands | Hotels, Casinos, Resorts | 89113 | 11,300,000,000 |
| 149 | Plano | Texas | Yum China s | Food Services | 75074 | 11,300,000,000 |
| 150 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 11,300,000,000 |
| 151 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 11,300,000,000 |
| 152 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 11,200,000,000 |
| 153 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 11,100,000,000 |
| 154 | Tampa | Florida | Mosaic | Chemicals | 33602 | 11,100,000,000 |
| 155 | Boston | Massachusetts | Vertex Pharmaceuticals | Pharmaceuticals | 02210 | 11,000,000,000 |
| 156 | Boston | Massachusetts | American Tower | Real Estate | 02116 | 11,000,000,000 |
| 157 | Minneapolis | Minnesota | Thrivent Financial for Lutherans | Insurance: Life, Health (Mutual) | 55415 | 10,900,000,000 |
| 158 | Raleigh | North Carolina | Advance Auto Parts | Specialty Retailers: Other | 27609 | 10,900,000,000 |
| 159 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 10,800,000,000 |
| 160 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 10,800,000,000 |
| 161 | Glen Allen | Virginia | Owens & Minor | Wholesalers: Health Care | 23060 | 10,700,000,000 |
| 162 | McLean | Virginia | Booz Allen Hamilton | Information Technology Services | 22102 | 10,700,000,000 |
| 163 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 10,700,000,000 |
| 164 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 10,600,000,000 |
| 165 | Bellevue | Washington | Expeditors International of Washington | Transportation and Logistics | 98006 | 10,600,000,000 |
| 166 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 10,600,000,000 |
| 167 | Tulsa | Oklahoma | Williams | Pipelines | 74172 | 10,500,000,000 |
| 168 | Jacksonville | Florida | Fidelity National Information | Financial Data Services | 32202 | 10,500,000,000 |
| 169 | Auburn Hills | Michigan | Autoliv | Motor Vehicles & Parts | 48326 | 10,400,000,000 |
| 170 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 10,400,000,000 |
| 171 | Newark | New Jersey | Public Service Enterprise | Utilities: Gas and Electric | 07102 | 10,300,000,000 |
| 172 | Maumee | Ohio | Dana | Motor Vehicles & Parts | 43537 | 10,300,000,000 |
| 173 | Victor | New York | Constellation Brands | Beverages | 14564 | 10,000,000,000 |
| 174 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 10,000,000,000 |
| 175 | Englewood | Colorado | QVC | Internet Services and Retailing | 80112 | 10,000,000,000 |
| 176 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 10,000,000,000 |
| 177 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 9,900,000,000 |
| 178 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 9,800,000,000 |
| 179 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 9,800,000,000 |
| 180 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 9,700,000,000 |
| 181 | Cambridge | Massachusetts | Biogen | Pharmaceuticals | 02142 | 9,700,000,000 |
| 182 | Newark | California | Concentrix | Information Technology Services | 94560 | 9,600,000,000 |
| 183 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 9,600,000,000 |
| 184 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 9,500,000,000 |
| 185 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 9,500,000,000 |
| 186 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 9,400,000,000 |
| 187 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 9,400,000,000 |
| 188 | Parsippany | New Jersey | Zoetis | Pharmaceuticals | 07054 | 9,300,000,000 |
| 189 | Denver | Colorado | Ovintiv | Mining, Crude-Oil Production | 80202 | 9,200,000,000 |
| 190 | Merriam | Kansas | Seaboard | Food Production | 66202 | 9,100,000,000 |
| 191 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 9,000,000,000 |
| 192 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 9,000,000,000 |
| 193 | Long Island City | New York | Altice USA | Telecommunications | 11101 | 9,000,000,000 |
| 194 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 8,800,000,000 |
| 195 | Washington | District of Columbia | Xylem | Industrial Machinery | 20003 | 8,600,000,000 |
| 196 | San Mateo | California | Franklin Resources | Securities | 94403 | 8,500,000,000 |
| 197 | Allentown | Pennsylvania | PPL | Utilities: Gas and Electric | 18101 | 8,500,000,000 |
| 198 | Lake Forest | Illinois | Packaging Corp. of America | Packaging, Containers | 60045 | 8,400,000,000 |
| 199 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 8,400,000,000 |
| 200 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 8,400,000,000 |
| 201 | Pleasanton | California | Workday | Computer Software | 94588 | 8,400,000,000 |
| 202 | Milwaukee | Wisconsin | Rockwell Automation | Electronics, Electrical Equip. | 53204 | 8,300,000,000 |
| 203 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 8,300,000,000 |
| 204 | Cincinnati | Ohio | American Financial | Insurance: Property and Casualty (Stock) | 45202 | 8,300,000,000 |
| 205 | Scottsdale | Arizona | Taylor Morrison Home | Homebuilders | 85251 | 8,200,000,000 |
| 206 | Chicago | Illinois | Old Republic International | Insurance: Property and Casualty (Stock) | 60601 | 8,200,000,000 |
| 207 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 8,200,000,000 |
| 208 | St. Paul | Minnesota | Securian Financial | Insurance: Life, Health (Stock) | 55101 | 8,200,000,000 |
| 209 | Greenwich | Connecticut | XPO | Transportation and Logistics | 06831 | 8,100,000,000 |
| 210 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 8,000,000,000 |
| 211 | Santa Clara | California | Palo Alto Networks | Network and Other Communications Equipment | 95054 | 8,000,000,000 |
| 212 | New York | New York | Voya Financial | Diversified Financials | 10169 | 8,000,000,000 |
| 213 | New York | New York | Foot Locker | Specialty Retailers: Apparel | 10001 | 8,000,000,000 |
| 214 | Toledo | Ohio | Welltower | Real Estate | 43615 | 8,000,000,000 |
| 215 | Irving | Texas | Commercial Metals | Metals | 75039 | 7,900,000,000 |
| 216 | Cleveland | Ohio | TransDigm | Aerospace & Defense | 44115 | 7,900,000,000 |
| 217 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 7,800,000,000 |
| 218 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 7,800,000,000 |
| 219 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 7,700,000,000 |
| 220 | San Francisco | California | Williams-Sonoma | Specialty Retailers: Other | 94109 | 7,700,000,000 |
| 221 | Phoenix | Arizona | Sprouts Farmers Market | Food & Drug Stores | 85054 | 7,700,000,000 |
| 222 | Houston | Texas | KBR | Information Technology Services | 77002 | 7,700,000,000 |
| 223 | Chandler | Arizona | Microchip Technology | Semiconductors and Other Electronic Components | 85224 | 7,600,000,000 |
| 224 | Redwood City | California | Electronic Arts | Entertainment | 94065 | 7,600,000,000 |
| 225 | Miami | Florida | Watsco | Wholesalers: Diversified | 33133 | 7,600,000,000 |
| 226 | San Jose | California | Sanmina | Semiconductors and Other Electronic Components | 95134 | 7,600,000,000 |
| 227 | Atlanta | Georgia | Newell Brands | Home Equipment, Furnishings | 30328 | 7,600,000,000 |
| 228 | Richmond | Virginia | ARKO | Specialty Retailers: Other | 23227 | 7,600,000,000 |
| 229 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 7,500,000,000 |
| 230 | Reston | Virginia | Science Applications International | Information Technology Services | 20190 | 7,500,000,000 |
| 231 | Corona | California | Monster Beverage | Beverages | 92879 | 7,500,000,000 |
| 232 | Beverly Hills | California | Endeavor | Entertainment | 90210 | 7,500,000,000 |
| 233 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 7,500,000,000 |
| 234 | Louisville | Kentucky | Yum Brands | Food Services | 40213 | 7,500,000,000 |
| 235 | Birmingham | Alabama | Vulcan Materials | Building Materials, Glass | 35242 | 7,400,000,000 |
| 236 | St. Louis | Missouri | Core & Main | Wholesalers: Diversified | 63146 | 7,400,000,000 |
| 237 | Westchester | Illinois | Ingredion | Food Production | 60154 | 7,400,000,000 |
| 238 | Pittsburgh | Pennsylvania | Howmet Aerospace | Aerospace & Defense | 15212 | 7,400,000,000 |
In [164]:
# Conclusion: fun fact about the Smallest Revenue Company in each City is Walmart is a Double Champion, both as the Biggest Revenue and the Smallest
# due to the fact that Walmart is the only Company in Bentonville goes into Fortune500 list.
In [167]:
# Join the Dataframe 'gdfusact' with 'dfminrevco' for the Top 10
gdfusactminrevco = gdfusact.merge(dfminrevco, how = 'inner', on = ['Zip Code'])
gdfusactminrevco = gdfusactminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [168]:
mctminrevco = gdfusactminrevco.explore(column='Revenue (rounded)', name='Smallest Revenue Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctminrevco)
mctminrevco
Out[168]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [169]:
# Check the Total Revenue in each City
dfcttr = df.groupby(['City','State'], as_index=False)[df.columns[[7]]].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfcttr
Out[169]:
| City | State | Revenue (rounded) | |
|---|---|---|---|
| 0 | New York | New York | 1,820,500,000,000 |
| 1 | Houston | Texas | 906,500,000,000 |
| 2 | Seattle | Washington | 744,900,000,000 |
| 3 | Bentonville | Arkansas | 681,000,000,000 |
| 4 | Atlanta | Georgia | 489,700,000,000 |
| 5 | Irving | Texas | 462,000,000,000 |
| 6 | Omaha | Nebraska | 427,000,000,000 |
| 7 | Eden Prairie | Minnesota | 418,000,000,000 |
| 8 | Cupertino | California | 391,000,000,000 |
| 9 | Spring | Texas | 379,700,000,000 |
| 10 | Woonsocket | Rhode Island | 372,800,000,000 |
| 11 | Chicago | Illinois | 368,100,000,000 |
| 12 | Dallas | Texas | 366,500,000,000 |
| 13 | Mountain View | California | 366,300,000,000 |
| 14 | Charlotte | North Carolina | 331,300,000,000 |
| 15 | San Francisco | California | 296,000,000,000 |
| 16 | Conshohocken | Pennsylvania | 294,000,000,000 |
| 17 | Cincinnati | Ohio | 276,100,000,000 |
| 18 | Santa Clara | California | 255,600,000,000 |
| 19 | Issaquah | Washington | 254,500,000,000 |
| 20 | Bloomfield | Connecticut | 247,100,000,000 |
| 21 | Redmond | Washington | 245,100,000,000 |
| 22 | Indianapolis | Indiana | 238,900,000,000 |
| 23 | Dublin | Ohio | 226,800,000,000 |
| 24 | Detroit | Michigan | 216,300,000,000 |
| 25 | Minneapolis | Minnesota | 211,400,000,000 |
| 26 | St. Louis | Missouri | 207,500,000,000 |
| 27 | McLean | Virginia | 197,900,000,000 |
| 28 | Washington | District of Columbia | 185,200,000,000 |
| 29 | Dearborn | Michigan | 185,000,000,000 |
| 30 | San Antonio | Texas | 172,600,000,000 |
| 31 | Menlo Park | California | 164,500,000,000 |
| 32 | Deerfield | Illinois | 162,800,000,000 |
| 33 | Arlington | Virginia | 159,500,000,000 |
| 34 | San Jose | California | 153,000,000,000 |
| 35 | Austin | Texas | 150,700,000,000 |
| 36 | Philadelphia | Pennsylvania | 141,100,000,000 |
| 37 | Findlay | Ohio | 140,400,000,000 |
| 38 | Louisville | Kentucky | 136,600,000,000 |
| 39 | Stamford | Connecticut | 132,500,000,000 |
| 40 | Richmond | Virginia | 127,000,000,000 |
| 41 | Memphis | Tennessee | 124,800,000,000 |
| 42 | Bloomington | Illinois | 123,000,000,000 |
| 43 | Purchase | New York | 120,100,000,000 |
| 44 | Pittsburgh | Pennsylvania | 119,200,000,000 |
| 45 | Boston | Massachusetts | 106,400,000,000 |
| 46 | Palo Alto | California | 106,000,000,000 |
| 47 | Boise | Idaho | 104,300,000,000 |
| 48 | Milwaukee | Wisconsin | 96,700,000,000 |
| 49 | Bethesda | Maryland | 96,100,000,000 |
| 50 | Round Rock | Texas | 95,600,000,000 |
| 51 | Burbank | California | 91,400,000,000 |
| 52 | Reston | Virginia | 90,300,000,000 |
| 53 | Columbus | Ohio | 90,300,000,000 |
| 54 | New Brunswick | New Jersey | 88,800,000,000 |
| 55 | Miami | Florida | 85,200,000,000 |
| 56 | Mooresville | North Carolina | 83,700,000,000 |
| 57 | Newark | New Jersey | 80,700,000,000 |
| 58 | Cleveland | Ohio | 79,300,000,000 |
| 59 | Mayfield Village | Ohio | 75,400,000,000 |
| 60 | Fremont | California | 73,400,000,000 |
| 61 | Phoenix | Arizona | 73,000,000,000 |
| 62 | Jacksonville | Florida | 71,700,000,000 |
| 63 | Nashville | Tennessee | 70,600,000,000 |
| 64 | San Diego | California | 64,600,000,000 |
| 65 | Rahway | New Jersey | 64,200,000,000 |
| 66 | Northbrook | Illinois | 64,100,000,000 |
| 67 | Armonk | New York | 62,800,000,000 |
| 68 | Lakeland | Florida | 60,200,000,000 |
| 69 | Waltham | Massachusetts | 60,100,000,000 |
| 70 | Providence | Rhode Island | 57,100,000,000 |
| 71 | Framingham | Massachusetts | 56,400,000,000 |
| 72 | North Chicago | Illinois | 56,300,000,000 |
| 73 | Springfield | Massachusetts | 55,000,000,000 |
| 74 | Parsippany | New Jersey | 54,200,000,000 |
| 75 | Fort Worth | Texas | 54,200,000,000 |
| 76 | Springdale | Arkansas | 53,300,000,000 |
| 77 | Moline | Illinois | 51,700,000,000 |
| 78 | Beaverton | Oregon | 51,400,000,000 |
| 79 | Denver | Colorado | 51,200,000,000 |
| 80 | St. Paul | Minnesota | 48,500,000,000 |
| 81 | Oakland | California | 48,500,000,000 |
| 82 | Princeton | New Jersey | 48,300,000,000 |
| 83 | Irvine | California | 48,000,000,000 |
| 84 | Cambridge | Massachusetts | 44,600,000,000 |
| 85 | Bellevue | Washington | 44,300,000,000 |
| 86 | St. Petersburg | Florida | 43,800,000,000 |
| 87 | Midland | Michigan | 43,000,000,000 |
| 88 | Greenwich | Connecticut | 42,800,000,000 |
| 89 | Abbott Park | Illinois | 42,000,000,000 |
| 90 | Richfield | Minnesota | 41,500,000,000 |
| 91 | Newport News | Virginia | 41,100,000,000 |
| 92 | Falls Church | Virginia | 41,000,000,000 |
| 93 | Long Beach | California | 40,600,000,000 |
| 94 | Goodlettsville | Tennessee | 40,600,000,000 |
| 95 | Inver Grove Heights | Minnesota | 39,300,000,000 |
| 96 | Los Gatos | California | 39,000,000,000 |
| 97 | Evendale | Ohio | 38,700,000,000 |
| 98 | Norwalk | Connecticut | 38,300,000,000 |
| 99 | Rosemont | Illinois | 37,900,000,000 |
| 100 | Marlborough | Massachusetts | 37,200,000,000 |
| 101 | Arlington | Texas | 36,800,000,000 |
| 102 | Medford | Oregon | 36,600,000,000 |
| 103 | Columbus | Indiana | 34,100,000,000 |
| 104 | Thousand Oaks | California | 33,400,000,000 |
| 105 | Tulsa | Oklahoma | 32,200,000,000 |
| 106 | Akron | Ohio | 31,900,000,000 |
| 107 | Chesapeake | Virginia | 30,800,000,000 |
| 108 | Beverly Hills | California | 30,700,000,000 |
| 109 | Bloomfield Hills | Michigan | 30,500,000,000 |
| 110 | Duluth | Georgia | 28,900,000,000 |
| 111 | Foster City | California | 28,800,000,000 |
| 112 | Las Vegas | Nevada | 28,500,000,000 |
| 113 | Centennial | Colorado | 27,900,000,000 |
| 114 | Brentwood | Tennessee | 27,400,000,000 |
| 115 | Glen Allen | Virginia | 27,300,000,000 |
| 116 | Newport Beach | California | 27,100,000,000 |
| 117 | Fort Lauderdale | Florida | 26,800,000,000 |
| 118 | Hartford | Connecticut | 26,500,000,000 |
| 119 | Westlake | Texas | 26,000,000,000 |
| 120 | Raleigh | North Carolina | 25,900,000,000 |
| 121 | Englewood | Colorado | 25,800,000,000 |
| 122 | Lake Forest | Illinois | 25,600,000,000 |
| 123 | Coral Gables | Florida | 24,900,000,000 |
| 124 | Juno Beach | Florida | 24,800,000,000 |
| 125 | Palm Beach Gardens | Florida | 24,800,000,000 |
| 126 | Auburn Hills | Michigan | 24,500,000,000 |
| 127 | Riverwoods | Illinois | 23,600,000,000 |
| 128 | Baltimore | Maryland | 23,600,000,000 |
| 129 | Southfield | Michigan | 23,300,000,000 |
| 130 | Tampa | Florida | 22,900,000,000 |
| 131 | Portage | Michigan | 22,600,000,000 |
| 132 | Chesterfield | Missouri | 22,100,000,000 |
| 133 | Scottsdale | Arizona | 22,000,000,000 |
| 134 | Maumee | Ohio | 21,600,000,000 |
| 135 | Melbourne | Florida | 21,300,000,000 |
| 136 | Madison | Wisconsin | 21,300,000,000 |
| 137 | Dublin | California | 21,100,000,000 |
| 138 | Vernon Hills | Illinois | 21,000,000,000 |
| 139 | Allentown | Pennsylvania | 20,600,000,000 |
| 140 | Franklin Lakes | New Jersey | 20,200,000,000 |
| 141 | Teaneck | New Jersey | 19,700,000,000 |
| 142 | Roseland | New Jersey | 19,200,000,000 |
| 143 | Toledo | Ohio | 19,000,000,000 |
| 144 | Columbus | Georgia | 18,900,000,000 |
| 145 | Radnor | Pennsylvania | 18,400,000,000 |
| 146 | Long Island City | New York | 18,300,000,000 |
| 147 | El Dorado | Arkansas | 17,900,000,000 |
| 148 | Rosemead | California | 17,600,000,000 |
| 149 | Fort Wayne | Indiana | 17,500,000,000 |
| 150 | Birmingham | Alabama | 16,800,000,000 |
| 151 | Springfield | Missouri | 16,700,000,000 |
| 152 | Benton Harbor | Michigan | 16,600,000,000 |
| 153 | Redwood City | California | 16,300,000,000 |
| 154 | Chandler | Arizona | 16,300,000,000 |
| 155 | Des Peres | Missouri | 16,300,000,000 |
| 156 | Menomonee Falls | Wisconsin | 16,200,000,000 |
| 157 | Arden Hills | Minnesota | 16,200,000,000 |
| 158 | Des Moines | Iowa | 16,100,000,000 |
| 159 | Oklahoma City | Oklahoma | 15,900,000,000 |
| 160 | Glenview | Illinois | 15,900,000,000 |
| 161 | King of Prussia | Pennsylvania | 15,800,000,000 |
| 162 | Lansing | Michigan | 15,800,000,000 |
| 163 | Woodland Hills | California | 15,500,000,000 |
| 164 | Summit | New Jersey | 15,500,000,000 |
| 165 | Burlington | Massachusetts | 15,400,000,000 |
| 166 | Durham | North Carolina | 15,400,000,000 |
| 167 | New Britain | Connecticut | 15,400,000,000 |
| 168 | Wallingford | Connecticut | 15,200,000,000 |
| 169 | Ankeny | Iowa | 14,900,000,000 |
| 170 | Canonsburg | Pennsylvania | 14,700,000,000 |
| 171 | Antioch | Tennessee | 14,400,000,000 |
| 172 | Farmington | Connecticut | 14,300,000,000 |
| 173 | Tarrytown | New York | 14,200,000,000 |
| 174 | Tempe | Arizona | 13,700,000,000 |
| 175 | Ashburn | Virginia | 13,700,000,000 |
| 176 | Buffalo | New York | 13,500,000,000 |
| 177 | Coraopolis | Pennsylvania | 13,400,000,000 |
| 178 | Erie | Pennsylvania | 13,200,000,000 |
| 179 | Monroe | Louisiana | 13,100,000,000 |
| 180 | Corning | New York | 13,100,000,000 |
| 181 | Burlington | North Carolina | 13,000,000,000 |
| 182 | Chattanooga | Tennessee | 12,900,000,000 |
| 183 | Melville | New York | 12,700,000,000 |
| 184 | Franklin | Tennessee | 12,600,000,000 |
| 185 | Wilmington | Delaware | 12,400,000,000 |
| 186 | Evansville | Indiana | 12,300,000,000 |
| 187 | Westminster | Colorado | 12,100,000,000 |
| 188 | Lowell | Arkansas | 12,100,000,000 |
| 189 | Plantation | Florida | 11,900,000,000 |
| 190 | Austin | Minnesota | 11,900,000,000 |
| 191 | New Orleans | Louisiana | 11,900,000,000 |
| 192 | Rolling Meadows | Illinois | 11,600,000,000 |
| 193 | Orlando | Florida | 11,400,000,000 |
| 194 | Reno | Nevada | 11,300,000,000 |
| 195 | Plano | Texas | 11,300,000,000 |
| 196 | Fairfield | Ohio | 11,300,000,000 |
| 197 | Bolingbrook | Illinois | 11,300,000,000 |
| 198 | Hershey | Pennsylvania | 11,200,000,000 |
| 199 | Midland | Texas | 11,100,000,000 |
| 200 | Calhoun | Georgia | 10,800,000,000 |
| 201 | Fort Washington | Pennsylvania | 10,800,000,000 |
| 202 | Oshkosh | Wisconsin | 10,700,000,000 |
| 203 | Burlington | New Jersey | 10,600,000,000 |
| 204 | Sumner | Washington | 10,600,000,000 |
| 205 | Johnston | Rhode Island | 10,400,000,000 |
| 206 | Victor | New York | 10,000,000,000 |
| 207 | Elkhart | Indiana | 10,000,000,000 |
| 208 | Sunny Isles Beach | Florida | 10,000,000,000 |
| 209 | Secaucus | New Jersey | 9,900,000,000 |
| 210 | Milpitas | California | 9,800,000,000 |
| 211 | Herndon | Virginia | 9,800,000,000 |
| 212 | El Segundo | California | 9,700,000,000 |
| 213 | Newark | California | 9,600,000,000 |
| 214 | Camden | New Jersey | 9,600,000,000 |
| 215 | Byron Center | Michigan | 9,500,000,000 |
| 216 | Oak Brook | Illinois | 9,500,000,000 |
| 217 | Kingsport | Tennessee | 9,400,000,000 |
| 218 | Wilmington | Massachusetts | 9,400,000,000 |
| 219 | Merriam | Kansas | 9,100,000,000 |
| 220 | Estero | Florida | 9,000,000,000 |
| 221 | Manhattan Beach | California | 9,000,000,000 |
| 222 | Mentor | Ohio | 8,800,000,000 |
| 223 | San Mateo | California | 8,500,000,000 |
| 224 | Pleasanton | California | 8,400,000,000 |
| 225 | Sunnyvale | California | 8,400,000,000 |
| 226 | Downers Grove | Illinois | 8,400,000,000 |
| 227 | Maplewood | Minnesota | 8,300,000,000 |
| 228 | Orrville | Ohio | 8,200,000,000 |
| 229 | Westerville | Ohio | 8,000,000,000 |
| 230 | Livonia | Michigan | 7,800,000,000 |
| 231 | New Braunfels | Texas | 7,800,000,000 |
| 232 | Warsaw | Indiana | 7,700,000,000 |
| 233 | Jackson | Michigan | 7,500,000,000 |
| 234 | Winona | Minnesota | 7,500,000,000 |
| 235 | Corona | California | 7,500,000,000 |
| 236 | Westchester | Illinois | 7,400,000,000 |
In [170]:
# Join the Dataframe 'gdfusact' with 'dfcttr' for the Top 10
dfcttr = dfcttr.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactcttr = gdfusact.merge(dfcttr, how = 'inner', on = ['Zip Code'])
gdfusactcttr = gdfusactcttr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [171]:
mcttr = gdfusactcttr.explore(column='Revenue (rounded)', name='Total Revenue in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mcttr)
mcttr
Out[171]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [172]:
# Average revenue in each City
dfctavr = df.groupby(['City','State'], as_index=False)[df.columns[[7]]].mean('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfctavr
Out[172]:
| City | State | Revenue (rounded) | |
|---|---|---|---|
| 0 | Bentonville | Arkansas | 681,000,000,000 |
| 1 | Cupertino | California | 391,000,000,000 |
| 2 | Woonsocket | Rhode Island | 372,800,000,000 |
| 3 | Conshohocken | Pennsylvania | 294,000,000,000 |
| 4 | Issaquah | Washington | 254,500,000,000 |
| 5 | Bloomfield | Connecticut | 247,100,000,000 |
| 6 | Redmond | Washington | 245,100,000,000 |
| 7 | Dublin | Ohio | 226,800,000,000 |
| 8 | Eden Prairie | Minnesota | 209,000,000,000 |
| 9 | Spring | Texas | 189,850,000,000 |
| 10 | Dearborn | Michigan | 185,000,000,000 |
| 11 | Mountain View | California | 183,150,000,000 |
| 12 | Menlo Park | California | 164,500,000,000 |
| 13 | Findlay | Ohio | 140,400,000,000 |
| 14 | Seattle | Washington | 124,150,000,000 |
| 15 | Bloomington | Illinois | 123,000,000,000 |
| 16 | Omaha | Nebraska | 106,750,000,000 |
| 17 | Round Rock | Texas | 95,600,000,000 |
| 18 | Burbank | California | 91,400,000,000 |
| 19 | New Brunswick | New Jersey | 88,800,000,000 |
| 20 | San Antonio | Texas | 86,300,000,000 |
| 21 | Mooresville | North Carolina | 83,700,000,000 |
| 22 | Deerfield | Illinois | 81,400,000,000 |
| 23 | Indianapolis | Indiana | 79,633,333,333 |
| 24 | Mayfield Village | Ohio | 75,400,000,000 |
| 25 | Austin | Texas | 75,350,000,000 |
| 26 | Detroit | Michigan | 72,100,000,000 |
| 27 | Nashville | Tennessee | 70,600,000,000 |
| 28 | Philadelphia | Pennsylvania | 70,550,000,000 |
| 29 | Rahway | New Jersey | 64,200,000,000 |
| 30 | Northbrook | Illinois | 64,100,000,000 |
| 31 | Armonk | New York | 62,800,000,000 |
| 32 | Washington | District of Columbia | 61,733,333,333 |
| 33 | Lakeland | Florida | 60,200,000,000 |
| 34 | Purchase | New York | 60,050,000,000 |
| 35 | Irving | Texas | 57,750,000,000 |
| 36 | Framingham | Massachusetts | 56,400,000,000 |
| 37 | North Chicago | Illinois | 56,300,000,000 |
| 38 | Charlotte | North Carolina | 55,216,666,667 |
| 39 | Fort Worth | Texas | 54,200,000,000 |
| 40 | Springdale | Arkansas | 53,300,000,000 |
| 41 | Arlington | Virginia | 53,166,666,667 |
| 42 | Palo Alto | California | 53,000,000,000 |
| 43 | Boise | Idaho | 52,150,000,000 |
| 44 | Moline | Illinois | 51,700,000,000 |
| 45 | Beaverton | Oregon | 51,400,000,000 |
| 46 | McLean | Virginia | 49,475,000,000 |
| 47 | Princeton | New Jersey | 48,300,000,000 |
| 48 | Bethesda | Maryland | 48,050,000,000 |
| 49 | Irvine | California | 48,000,000,000 |
| 50 | Cincinnati | Ohio | 46,016,666,667 |
| 51 | Louisville | Kentucky | 45,533,333,333 |
| 52 | Midland | Michigan | 43,000,000,000 |
| 53 | Santa Clara | California | 42,600,000,000 |
| 54 | New York | New York | 42,337,209,302 |
| 55 | Abbott Park | Illinois | 42,000,000,000 |
| 56 | Memphis | Tennessee | 41,600,000,000 |
| 57 | St. Louis | Missouri | 41,500,000,000 |
| 58 | Richfield | Minnesota | 41,500,000,000 |
| 59 | Falls Church | Virginia | 41,000,000,000 |
| 60 | Dallas | Texas | 40,722,222,222 |
| 61 | Long Beach | California | 40,600,000,000 |
| 62 | Goodlettsville | Tennessee | 40,600,000,000 |
| 63 | Newark | New Jersey | 40,350,000,000 |
| 64 | Inver Grove Heights | Minnesota | 39,300,000,000 |
| 65 | Los Gatos | California | 39,000,000,000 |
| 66 | Evendale | Ohio | 38,700,000,000 |
| 67 | Rosemont | Illinois | 37,900,000,000 |
| 68 | Houston | Texas | 37,770,833,333 |
| 69 | Atlanta | Georgia | 37,669,230,769 |
| 70 | Arlington | Texas | 36,800,000,000 |
| 71 | Fremont | California | 36,700,000,000 |
| 72 | Medford | Oregon | 36,600,000,000 |
| 73 | Minneapolis | Minnesota | 35,233,333,333 |
| 74 | Columbus | Indiana | 34,100,000,000 |
| 75 | Thousand Oaks | California | 33,400,000,000 |
| 76 | Stamford | Connecticut | 33,125,000,000 |
| 77 | San Francisco | California | 32,888,888,889 |
| 78 | Chesapeake | Virginia | 30,800,000,000 |
| 79 | Bloomfield Hills | Michigan | 30,500,000,000 |
| 80 | Columbus | Ohio | 30,100,000,000 |
| 81 | Waltham | Massachusetts | 30,050,000,000 |
| 82 | Foster City | California | 28,800,000,000 |
| 83 | Miami | Florida | 28,400,000,000 |
| 84 | Centennial | Colorado | 27,900,000,000 |
| 85 | Springfield | Massachusetts | 27,500,000,000 |
| 86 | Fort Lauderdale | Florida | 26,800,000,000 |
| 87 | Hartford | Connecticut | 26,500,000,000 |
| 88 | Chicago | Illinois | 26,292,857,143 |
| 89 | Westlake | Texas | 26,000,000,000 |
| 90 | Richmond | Virginia | 25,400,000,000 |
| 91 | Palm Beach Gardens | Florida | 24,800,000,000 |
| 92 | Juno Beach | Florida | 24,800,000,000 |
| 93 | Oakland | California | 24,250,000,000 |
| 94 | Baltimore | Maryland | 23,600,000,000 |
| 95 | Riverwoods | Illinois | 23,600,000,000 |
| 96 | Southfield | Michigan | 23,300,000,000 |
| 97 | Portage | Michigan | 22,600,000,000 |
| 98 | Cambridge | Massachusetts | 22,300,000,000 |
| 99 | Bellevue | Washington | 22,150,000,000 |
| 100 | Chesterfield | Missouri | 22,100,000,000 |
| 101 | St. Petersburg | Florida | 21,900,000,000 |
| 102 | San Jose | California | 21,857,142,857 |
| 103 | San Diego | California | 21,533,333,333 |
| 104 | Madison | Wisconsin | 21,300,000,000 |
| 105 | Melbourne | Florida | 21,300,000,000 |
| 106 | Boston | Massachusetts | 21,280,000,000 |
| 107 | Dublin | California | 21,100,000,000 |
| 108 | Vernon Hills | Illinois | 21,000,000,000 |
| 109 | Newport News | Virginia | 20,550,000,000 |
| 110 | Franklin Lakes | New Jersey | 20,200,000,000 |
| 111 | Teaneck | New Jersey | 19,700,000,000 |
| 112 | Milwaukee | Wisconsin | 19,340,000,000 |
| 113 | Roseland | New Jersey | 19,200,000,000 |
| 114 | Norwalk | Connecticut | 19,150,000,000 |
| 115 | Providence | Rhode Island | 19,033,333,333 |
| 116 | Columbus | Georgia | 18,900,000,000 |
| 117 | Marlborough | Massachusetts | 18,600,000,000 |
| 118 | Radnor | Pennsylvania | 18,400,000,000 |
| 119 | Phoenix | Arizona | 18,250,000,000 |
| 120 | Parsippany | New Jersey | 18,066,666,667 |
| 121 | Reston | Virginia | 18,060,000,000 |
| 122 | Jacksonville | Florida | 17,925,000,000 |
| 123 | El Dorado | Arkansas | 17,900,000,000 |
| 124 | Rosemead | California | 17,600,000,000 |
| 125 | Fort Wayne | Indiana | 17,500,000,000 |
| 126 | Pittsburgh | Pennsylvania | 17,028,571,429 |
| 127 | Springfield | Missouri | 16,700,000,000 |
| 128 | Benton Harbor | Michigan | 16,600,000,000 |
| 129 | Des Peres | Missouri | 16,300,000,000 |
| 130 | Menomonee Falls | Wisconsin | 16,200,000,000 |
| 131 | Arden Hills | Minnesota | 16,200,000,000 |
| 132 | St. Paul | Minnesota | 16,166,666,667 |
| 133 | Tulsa | Oklahoma | 16,100,000,000 |
| 134 | Des Moines | Iowa | 16,100,000,000 |
| 135 | Akron | Ohio | 15,950,000,000 |
| 136 | Glenview | Illinois | 15,900,000,000 |
| 137 | Oklahoma City | Oklahoma | 15,900,000,000 |
| 138 | Cleveland | Ohio | 15,860,000,000 |
| 139 | Lansing | Michigan | 15,800,000,000 |
| 140 | King of Prussia | Pennsylvania | 15,800,000,000 |
| 141 | Woodland Hills | California | 15,500,000,000 |
| 142 | Summit | New Jersey | 15,500,000,000 |
| 143 | Durham | North Carolina | 15,400,000,000 |
| 144 | Burlington | Massachusetts | 15,400,000,000 |
| 145 | New Britain | Connecticut | 15,400,000,000 |
| 146 | Beverly Hills | California | 15,350,000,000 |
| 147 | Wallingford | Connecticut | 15,200,000,000 |
| 148 | Ankeny | Iowa | 14,900,000,000 |
| 149 | Canonsburg | Pennsylvania | 14,700,000,000 |
| 150 | Duluth | Georgia | 14,450,000,000 |
| 151 | Antioch | Tennessee | 14,400,000,000 |
| 152 | Farmington | Connecticut | 14,300,000,000 |
| 153 | Las Vegas | Nevada | 14,250,000,000 |
| 154 | Tarrytown | New York | 14,200,000,000 |
| 155 | Ashburn | Virginia | 13,700,000,000 |
| 156 | Tempe | Arizona | 13,700,000,000 |
| 157 | Brentwood | Tennessee | 13,700,000,000 |
| 158 | Glen Allen | Virginia | 13,650,000,000 |
| 159 | Newport Beach | California | 13,550,000,000 |
| 160 | Buffalo | New York | 13,500,000,000 |
| 161 | Coraopolis | Pennsylvania | 13,400,000,000 |
| 162 | Erie | Pennsylvania | 13,200,000,000 |
| 163 | Corning | New York | 13,100,000,000 |
| 164 | Monroe | Louisiana | 13,100,000,000 |
| 165 | Burlington | North Carolina | 13,000,000,000 |
| 166 | Raleigh | North Carolina | 12,950,000,000 |
| 167 | Chattanooga | Tennessee | 12,900,000,000 |
| 168 | Englewood | Colorado | 12,900,000,000 |
| 169 | Denver | Colorado | 12,800,000,000 |
| 170 | Lake Forest | Illinois | 12,800,000,000 |
| 171 | Melville | New York | 12,700,000,000 |
| 172 | Franklin | Tennessee | 12,600,000,000 |
| 173 | Coral Gables | Florida | 12,450,000,000 |
| 174 | Wilmington | Delaware | 12,400,000,000 |
| 175 | Evansville | Indiana | 12,300,000,000 |
| 176 | Auburn Hills | Michigan | 12,250,000,000 |
| 177 | Westminster | Colorado | 12,100,000,000 |
| 178 | Lowell | Arkansas | 12,100,000,000 |
| 179 | Austin | Minnesota | 11,900,000,000 |
| 180 | Plantation | Florida | 11,900,000,000 |
| 181 | New Orleans | Louisiana | 11,900,000,000 |
| 182 | Rolling Meadows | Illinois | 11,600,000,000 |
| 183 | Tampa | Florida | 11,450,000,000 |
| 184 | Orlando | Florida | 11,400,000,000 |
| 185 | Reno | Nevada | 11,300,000,000 |
| 186 | Plano | Texas | 11,300,000,000 |
| 187 | Fairfield | Ohio | 11,300,000,000 |
| 188 | Bolingbrook | Illinois | 11,300,000,000 |
| 189 | Hershey | Pennsylvania | 11,200,000,000 |
| 190 | Midland | Texas | 11,100,000,000 |
| 191 | Scottsdale | Arizona | 11,000,000,000 |
| 192 | Calhoun | Georgia | 10,800,000,000 |
| 193 | Fort Washington | Pennsylvania | 10,800,000,000 |
| 194 | Maumee | Ohio | 10,800,000,000 |
| 195 | Greenwich | Connecticut | 10,700,000,000 |
| 196 | Oshkosh | Wisconsin | 10,700,000,000 |
| 197 | Burlington | New Jersey | 10,600,000,000 |
| 198 | Sumner | Washington | 10,600,000,000 |
| 199 | Johnston | Rhode Island | 10,400,000,000 |
| 200 | Allentown | Pennsylvania | 10,300,000,000 |
| 201 | Victor | New York | 10,000,000,000 |
| 202 | Sunny Isles Beach | Florida | 10,000,000,000 |
| 203 | Elkhart | Indiana | 10,000,000,000 |
| 204 | Secaucus | New Jersey | 9,900,000,000 |
| 205 | Milpitas | California | 9,800,000,000 |
| 206 | Herndon | Virginia | 9,800,000,000 |
| 207 | El Segundo | California | 9,700,000,000 |
| 208 | Newark | California | 9,600,000,000 |
| 209 | Camden | New Jersey | 9,600,000,000 |
| 210 | Toledo | Ohio | 9,500,000,000 |
| 211 | Oak Brook | Illinois | 9,500,000,000 |
| 212 | Byron Center | Michigan | 9,500,000,000 |
| 213 | Wilmington | Massachusetts | 9,400,000,000 |
| 214 | Kingsport | Tennessee | 9,400,000,000 |
| 215 | Long Island City | New York | 9,150,000,000 |
| 216 | Merriam | Kansas | 9,100,000,000 |
| 217 | Estero | Florida | 9,000,000,000 |
| 218 | Manhattan Beach | California | 9,000,000,000 |
| 219 | Mentor | Ohio | 8,800,000,000 |
| 220 | San Mateo | California | 8,500,000,000 |
| 221 | Pleasanton | California | 8,400,000,000 |
| 222 | Downers Grove | Illinois | 8,400,000,000 |
| 223 | Birmingham | Alabama | 8,400,000,000 |
| 224 | Sunnyvale | California | 8,400,000,000 |
| 225 | Maplewood | Minnesota | 8,300,000,000 |
| 226 | Orrville | Ohio | 8,200,000,000 |
| 227 | Redwood City | California | 8,150,000,000 |
| 228 | Chandler | Arizona | 8,150,000,000 |
| 229 | Westerville | Ohio | 8,000,000,000 |
| 230 | Livonia | Michigan | 7,800,000,000 |
| 231 | New Braunfels | Texas | 7,800,000,000 |
| 232 | Warsaw | Indiana | 7,700,000,000 |
| 233 | Jackson | Michigan | 7,500,000,000 |
| 234 | Corona | California | 7,500,000,000 |
| 235 | Winona | Minnesota | 7,500,000,000 |
| 236 | Westchester | Illinois | 7,400,000,000 |
In [173]:
# Fun fact: again, Bentonville is the Champion due to the only one Company made it into Fortune500 list.
In [174]:
# Join the Dataframe 'gdfusact' with 'dfctavr' for the Top 10
dfctavr = dfctavr.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctavr = gdfusact.merge(dfctavr, how = 'inner', on = ['Zip Code'])
gdfusactctavr = gdfusactctavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [175]:
mctctavr = gdfusactctavr.explore(column='Revenue (rounded)', name='Average Revenue in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctctavr)
mctctavr
Out[175]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [176]:
# Check the Largest Employer Company in each City
dfmaxempco = df.head(1)
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
mnmaxemp = dfct['Employees'].max()
dfctmaxempco = dfct.where(dfct['Employees'] == mnmaxemp).dropna()
dfmaxempco = pd.concat([dfmaxempco, dfctmaxempco], ignore_index=True)
dfmaxempco = dfmaxempco.drop(0)
dfmaxempco[['City','State','Company','Industry','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[176]:
| City | State | Company | Industry | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 2,100,000 |
| 1 | Seattle | Washington | Amazon | Internet Services and Retailing | 98109 | 1,556,000 |
| 2 | Atlanta | Georgia | Home Depot | Specialty Retailers: Other | 30339 | 470,100 |
| 3 | Newark | California | Concentrix | Information Technology Services | 94560 | 450,000 |
| 4 | Minneapolis | Minnesota | Target | General Merchandisers | 55403 | 440,000 |
| 5 | Memphis | Tennessee | FedEx | Mail, Package and Freight Delivery | 38120 | 422,100 |
| 6 | Cincinnati | Ohio | Kroger | Food & Drug Stores | 45202 | 409,000 |
| 7 | Eden Prairie | Minnesota | UnitedHealth | Health Care: Insurance and Managed Care | 55344 | 400,000 |
| 8 | Omaha | Nebraska | Berkshire Hathaway | Insurance: Property and Casualty (Stock) | 68131 | 392,400 |
| 9 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 364,000 |
| 10 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 336,800 |
| 11 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 333,000 |
| 12 | Purchase | New York | PepsiCo | Food Consumer Products | 10577 | 319,000 |
| 13 | New York | New York | JPMorgan Chase | Commercial Banks | 10017 | 317,200 |
| 14 | Armonk | New York | IBM | Information Technology Services | 10504 | 284,500 |
| 15 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 271,000 |
| 16 | Philadelphia | Pennsylvania | Aramark | Diversified Outsourcing Services | 19103 | 266,700 |
| 17 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 259,500 |
| 18 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 255,000 |
| 19 | Deerfield | Illinois | Walgreens | Food & Drug Stores | 60015 | 252,500 |
| 20 | Plano | Texas | Yum China s | Food Services | 75074 | 245,500 |
| 21 | Redmond | Washington | Microsoft | Computer Software | 98052 | 228,000 |
| 22 | San Francisco | California | Wells Fargo | Commercial Banks | 94104 | 217,500 |
| 23 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 215,500 |
| 24 | Charlotte | North Carolina | Bank of America | Commercial Banks | 28255 | 213,200 |
| 25 | Burbank | California | Walt Disney | Entertainment | 91521 | 205,000 |
| 26 | Boise | Idaho | Albertsons | Food & Drug Stores | 83706 | 196,600 |
| 27 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 194,200 |
| 28 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 191,100 |
| 29 | Arlington | Virginia | RTX | Aerospace & Defense | 22209 | 186,000 |
| 30 | Mountain View | California | Alphabet | Internet Services and Retailing | 94043 | 183,300 |
| 31 | McLean | Virginia | Hilton | Hotels, Casinos, Resorts | 22102 | 181,000 |
| 32 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 173,700 |
| 33 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 171,000 |
| 34 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 164,000 |
| 35 | Detroit | Michigan | General Motors | Motor Vehicles & Parts | 48265 | 162,000 |
| 36 | Austin | Texas | Oracle | Computer Software | 78741 | 159,000 |
| 37 | Bethesda | Maryland | Marriott International | Hotels, Casinos, Resorts | 20814 | 155,000 |
| 38 | Chicago | Illinois | McDonald's | Food Services | 60607 | 150,000 |
| 39 | Dallas | Texas | AT&T | Telecommunications | 75202 | 141,000 |
| 40 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 139,600 |
| 41 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 138,100 |
| 42 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 138,000 |
| 43 | St. Petersburg | Florida | Jabil | Semiconductors and Other Electronic Components | 33716 | 138,000 |
| 44 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 133,300 |
| 45 | Newport Beach | California | Chipotle Mexican Grill | Food Services | 92660 | 130,500 |
| 46 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 130,000 |
| 47 | Greenwich | Connecticut | GXO Logistics | Transportation and Logistics | 06831 | 128,500 |
| 48 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 125,000 |
| 49 | Waltham | Massachusetts | Thermo Fisher Scientific | Scientific, Photographic and Control Equipment | 02451 | 125,000 |
| 50 | Reston | Virginia | General Dynamics | Aerospace & Defense | 20190 | 117,000 |
| 51 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 114,000 |
| 52 | Irving | Texas | Caterpillar | Construction and Farm Machinery | 75039 | 112,900 |
| 53 | Santa Clara | California | Intel | Semiconductors and Other Electronic Components | 95054 | 108,900 |
| 54 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 108,000 |
| 55 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 107,000 |
| 56 | Indianapolis | Indiana | Elevance Health | Health Care: Insurance and Managed Care | 46204 | 103,700 |
| 57 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 97,000 |
| 58 | Stamford | Connecticut | Charter Communications | Telecommunications | 06902 | 94,500 |
| 59 | San Jose | California | Cisco Systems | Network and Other Communications Equipment | 95134 | 90,400 |
| 60 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 88,000 |
| 61 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 87,500 |
| 62 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 85,600 |
| 63 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 85,000 |
| 64 | Beaverton | Oregon | Nike | Apparel | 97005 | 79,400 |
| 65 | Cambridge | Massachusetts | GE Vernova | Energy | 02141 | 76,800 |
| 66 | Houston | Texas | Sysco | Wholesalers: Food and Grocery | 77077 | 76,000 |
| 67 | Denver | Colorado | DaVita | Health Care: Medical Facilities | 80202 | 76,000 |
| 68 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 74,100 |
| 69 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 74,000 |
| 70 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 74,000 |
| 71 | St. Louis | Missouri | Emerson Electric | Industrial Machinery | 63136 | 73,000 |
| 72 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 72,400 |
| 73 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 72,000 |
| 74 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 69,600 |
| 75 | Las Vegas | Nevada | MGM Resorts International | Hotels, Casinos, Resorts | 89109 | 69,000 |
| 76 | Akron | Ohio | Goodyear Tire & Rubber | Motor Vehicles & Parts | 44316 | 68,000 |
| 77 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 67,400 |
| 78 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 66,300 |
| 79 | Louisville | Kentucky | Humana | Health Care: Insurance and Managed Care | 40202 | 65,700 |
| 80 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 65,400 |
| 81 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 64,000 |
| 82 | Cleveland | Ohio | Sherwin-Williams | Chemicals | 44115 | 63,900 |
| 83 | Auburn Hills | Michigan | Autoliv | Motor Vehicles & Parts | 48326 | 62,300 |
| 84 | Washington | District of Columbia | Danaher | Medical Products and Equipment | 20037 | 62,000 |
| 85 | St. Paul | Minnesota | 3M | Chemicals | 55144 | 61,500 |
| 86 | Spring | Texas | Hewlett Packard | Computers, Office Equipment | 77389 | 61,000 |
| 87 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 60,000 |
| 88 | Palo Alto | California | HP | Computers, Office Equipment | 94304 | 58,000 |
| 89 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 56,300 |
| 90 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 56,000 |
| 91 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 55,500 |
| 92 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 55,200 |
| 93 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 55,000 |
| 94 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 55,000 |
| 95 | Pittsburgh | Pennsylvania | PNC | Commercial Banks | 15222 | 54,400 |
| 96 | Marlborough | Massachusetts | Boston Scientific | Medical Products and Equipment | 01752 | 53,000 |
| 97 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 53,000 |
| 98 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 53,000 |
| 99 | Boston | Massachusetts | State Street | Commercial Banks | 02114 | 52,600 |
| 100 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 52,500 |
| 101 | Coral Gables | Florida | Ryder System | Transportation and Logistics | 33134 | 50,700 |
| 102 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 50,500 |
| 103 | Jacksonville | Florida | Fidelity National Information | Financial Data Services | 32202 | 50,000 |
| 104 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 50,000 |
| 105 | San Diego | California | Qualcomm | Semiconductors and Other Electronic Components | 92121 | 49,000 |
| 106 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 48,500 |
| 107 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 48,400 |
| 108 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 48,000 |
| 109 | Raleigh | North Carolina | Advance Auto Parts | Specialty Retailers: Other | 27609 | 48,000 |
| 110 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 47,300 |
| 111 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 47,000 |
| 112 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 47,000 |
| 113 | Newport News | Virginia | Huntington Ingalls Industries | Aerospace & Defense | 23607 | 44,000 |
| 114 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 44,000 |
| 115 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 44,000 |
| 116 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 44,000 |
| 117 | Phoenix | Arizona | Republic Services | Waste Management | 85054 | 42,000 |
| 118 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 42,000 |
| 119 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 41,900 |
| 120 | Norwalk | Connecticut | EMCOR | Engineering & Construction | 06851 | 40,400 |
| 121 | Maumee | Ohio | Dana | Motor Vehicles & Parts | 43537 | 39,600 |
| 122 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 39,000 |
| 123 | Brentwood | Tennessee | Tractor Supply | Specialty Retailers: Other | 37027 | 39,000 |
| 124 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 39,000 |
| 125 | San Antonio | Texas | USAA | Insurance: Property and Casualty (Stock) | 78288 | 38,000 |
| 126 | Milwaukee | Wisconsin | Fiserv | Financial Data Services | 53203 | 38,000 |
| 127 | Newark | New Jersey | Prudential Financial | Insurance: Life, Health (Stock) | 07102 | 37,900 |
| 128 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 37,400 |
| 129 | Richmond | Virginia | Performance Food | Wholesalers: Food and Grocery | 23238 | 36,800 |
| 130 | Midland | Michigan | Dow | Chemicals | 48674 | 36,000 |
| 131 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 35,000 |
| 132 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 34,100 |
| 133 | Providence | Rhode Island | Textron | Aerospace & Defense | 02903 | 34,000 |
| 134 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 33,600 |
| 135 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 33,100 |
| 136 | Westlake | Texas | Charles Schwab | Securities | 76262 | 32,100 |
| 137 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 32,000 |
| 138 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 31,000 |
| 139 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 30,200 |
| 140 | Bellevue | Washington | Paccar | Motor Vehicles & Parts | 98004 | 30,100 |
| 141 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 30,000 |
| 142 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 29,400 |
| 143 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 28,900 |
| 144 | Oakland | California | PG&E | Utilities: Gas and Electric | 94612 | 28,400 |
| 145 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 28,000 |
| 146 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 26,100 |
| 147 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 26,000 |
| 148 | Fremont | California | TD Synnex | Wholesalers: Electronics and Office Equipment | 94538 | 25,800 |
| 149 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 25,100 |
| 150 | Toledo | Ohio | Owens Corning | Building Materials, Glass | 43659 | 25,000 |
| 151 | Lake Forest | Illinois | W.W. Grainger | Wholesalers: Diversified | 60045 | 25,000 |
| 152 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 25,000 |
| 153 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 25,000 |
| 154 | Beverly Hills | California | Live Nation Entertainment | Entertainment | 90210 | 24,200 |
| 155 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 24,000 |
| 156 | Duluth | Georgia | AGCO | Construction and Farm Machinery | 30096 | 24,000 |
| 157 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 24,000 |
| 158 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 24,000 |
| 159 | Glen Allen | Virginia | Owens & Minor | Wholesalers: Health Care | 23060 | 23,200 |
| 160 | Tampa | Florida | Crown s | Packaging, Containers | 33637 | 23,000 |
| 161 | Columbus | Ohio | Nationwide | Insurance: Property and Casualty (Mutual) | 43215 | 22,500 |
| 162 | Allentown | Pennsylvania | Air Products & Chemicals | Chemicals | 18106 | 22,400 |
| 163 | Chandler | Arizona | Microchip Technology | Semiconductors and Other Electronic Components | 85224 | 22,300 |
| 164 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 22,300 |
| 165 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 22,100 |
| 166 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 22,000 |
| 167 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 22,000 |
| 168 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 21,500 |
| 169 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 21,000 |
| 170 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 21,000 |
| 171 | Pleasanton | California | Workday | Computer Software | 94588 | 20,500 |
| 172 | Parsippany | New Jersey | Avis Budget | Automotive Retailing, Services | 07054 | 20,500 |
| 173 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 20,000 |
| 174 | Long Island City | New York | JetBlue Airways | Airlines | 11101 | 19,800 |
| 175 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 19,700 |
| 176 | Birmingham | Alabama | Regions Financial | Commercial Banks | 35203 | 19,600 |
| 177 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 19,300 |
| 178 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 19,100 |
| 179 | Englewood | Colorado | QVC | Internet Services and Retailing | 80112 | 19,000 |
| 180 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 18,500 |
| 181 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 18,300 |
| 182 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 18,000 |
| 183 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 18,000 |
| 184 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 18,000 |
| 185 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 17,600 |
| 186 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 17,400 |
| 187 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 17,000 |
| 188 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 16,800 |
| 189 | Scottsdale | Arizona | Reliance | Metals | 85254 | 16,000 |
| 190 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 16,000 |
| 191 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 15,600 |
| 192 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 15,100 |
| 193 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 15,100 |
| 194 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 15,100 |
| 195 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 15,100 |
| 196 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 15,000 |
| 197 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 15,000 |
| 198 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 14,800 |
| 199 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 14,400 |
| 200 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 14,200 |
| 201 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 14,000 |
| 202 | Merriam | Kansas | Seaboard | Food Production | 66202 | 14,000 |
| 203 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 14,000 |
| 204 | Los Gatos | California | Netflix | Entertainment | 95032 | 14,000 |
| 205 | Redwood City | California | Electronic Arts | Entertainment | 94065 | 13,700 |
| 206 | Miami | Florida | Lennar | Homebuilders | 33126 | 13,300 |
| 207 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 13,000 |
| 208 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 12,700 |
| 209 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 12,500 |
| 210 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 12,300 |
| 211 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 11,600 |
| 212 | Springfield | Massachusetts | Mass Mutual | Insurance: Life, Health (Mutual) | 01111 | 11,200 |
| 213 | Westchester | Illinois | Ingredion | Food Production | 60154 | 11,200 |
| 214 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 11,100 |
| 215 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 10,900 |
| 216 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 10,700 |
| 217 | San Mateo | California | Franklin Resources | Securities | 94403 | 10,200 |
| 218 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 9,900 |
| 219 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 9,800 |
| 220 | Victor | New York | Constellation Brands | Beverages | 14564 | 9,300 |
| 221 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 9,000 |
| 222 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 9,000 |
| 223 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 8,300 |
| 224 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 8,100 |
| 225 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 7,900 |
| 226 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 7,300 |
| 227 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 6,700 |
| 228 | Corona | California | Monster Beverage | Beverages | 92879 | 6,000 |
| 229 | Tulsa | Oklahoma | Williams | Pipelines | 74172 | 5,800 |
| 230 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 5,800 |
| 231 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 5,600 |
| 232 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 4,900 |
| 233 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 4,100 |
| 234 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 2,300 |
| 235 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 2,000 |
| 236 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 500 |
In [177]:
# Join the Dataframe 'gdfusact' with 'dfmaxempco' for the Top 10
gdfusactmaxempco = gdfusact.merge(dfmaxempco, how = 'inner', on = ['Zip Code'])
gdfusactmaxempco = gdfusactmaxempco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [178]:
mctmaxempco = gdfusactmaxempco.explore(column='Revenue (rounded)', name='Biggest Employer Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxempco)
mctmaxempco
Out[178]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [182]:
# Check the Smallest Employer Company in each City
dfminempco = df.head(1)
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
mnminemp = dfct['Employees'].min()
dfctminempco = dfct.where(dfct['Employees'] == mnminemp).dropna()
dfminempco = pd.concat([dfminempco, dfctminempco], ignore_index=True)
dfminempco = dfminempco.drop(0)
dfminempco[['City','State','Company','Industry','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[182]:
| City | State | Company | Industry | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 2,100,000 |
| 1 | Newark | California | Concentrix | Information Technology Services | 94560 | 450,000 |
| 2 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 364,000 |
| 3 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 336,800 |
| 4 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 333,000 |
| 5 | Armonk | New York | IBM | Information Technology Services | 10504 | 284,500 |
| 6 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 271,000 |
| 7 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 259,500 |
| 8 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 255,000 |
| 9 | Plano | Texas | Yum China s | Food Services | 75074 | 245,500 |
| 10 | Redmond | Washington | Microsoft | Computer Software | 98052 | 228,000 |
| 11 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 215,500 |
| 12 | Burbank | California | Walt Disney | Entertainment | 91521 | 205,000 |
| 13 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 194,200 |
| 14 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 191,100 |
| 15 | Philadelphia | Pennsylvania | Comcast | Telecommunications | 19103 | 182,000 |
| 16 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 173,700 |
| 17 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 171,000 |
| 18 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 164,000 |
| 19 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 139,600 |
| 20 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 138,100 |
| 21 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 138,000 |
| 22 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 133,300 |
| 23 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 130,000 |
| 24 | Austin | Texas | Tesla | Motor Vehicles & Parts | 78725 | 125,700 |
| 25 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 125,000 |
| 26 | Bethesda | Maryland | Lockheed Martin | Aerospace & Defense | 20817 | 121,000 |
| 27 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 114,000 |
| 28 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 108,000 |
| 29 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 107,000 |
| 30 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 97,000 |
| 31 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 88,000 |
| 32 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 87,500 |
| 33 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 85,600 |
| 34 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 85,000 |
| 35 | Beaverton | Oregon | Nike | Apparel | 97005 | 79,400 |
| 36 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 74,100 |
| 37 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 74,000 |
| 38 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 74,000 |
| 39 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 72,400 |
| 40 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 72,000 |
| 41 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 69,600 |
| 42 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 67,400 |
| 43 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 66,300 |
| 44 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 65,400 |
| 45 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 64,000 |
| 46 | Spring | Texas | Exxon Mobil | Petroleum Refining | 77389 | 60,900 |
| 47 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 60,000 |
| 48 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 56,300 |
| 49 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 56,000 |
| 50 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 55,500 |
| 51 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 55,200 |
| 52 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 55,000 |
| 53 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 55,000 |
| 54 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 53,000 |
| 55 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 53,000 |
| 56 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 52,500 |
| 57 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 50,500 |
| 58 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 50,000 |
| 59 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 48,500 |
| 60 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 48,400 |
| 61 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 48,000 |
| 62 | Boise | Idaho | Micron Technology | Semiconductors and Other Electronic Components | 83716 | 48,000 |
| 63 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 47,300 |
| 64 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 47,000 |
| 65 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 47,000 |
| 66 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 44,000 |
| 67 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 44,000 |
| 68 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 44,000 |
| 69 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 42,000 |
| 70 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 41,900 |
| 71 | Las Vegas | Nevada | Las Vegas Sands | Hotels, Casinos, Resorts | 89113 | 40,100 |
| 72 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 39,000 |
| 73 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 39,000 |
| 74 | Auburn Hills | Michigan | BorgWarner | Motor Vehicles & Parts | 48326 | 38,300 |
| 75 | Deerfield | Illinois | Baxter International | Medical Products and Equipment | 60015 | 38,000 |
| 76 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 37,400 |
| 77 | Memphis | Tennessee | International Paper | Packaging, Containers | 38197 | 37,000 |
| 78 | Palo Alto | California | Broadcom | Semiconductors and Other Electronic Components | 94304 | 37,000 |
| 79 | Midland | Michigan | Dow | Chemicals | 48674 | 36,000 |
| 80 | Purchase | New York | Mastercard | Financial Data Services | 10577 | 35,300 |
| 81 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 35,000 |
| 82 | Newport News | Virginia | Ferguson | Wholesalers: Diversified | 23606 | 35,000 |
| 83 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 34,100 |
| 84 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 33,600 |
| 85 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 33,100 |
| 86 | Marlborough | Massachusetts | BJ's Wholesale Club | General Merchandisers | 01752 | 33,000 |
| 87 | Westlake | Texas | Charles Schwab | Securities | 76262 | 32,100 |
| 88 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 32,000 |
| 89 | Coral Gables | Florida | MasTec | Engineering & Construction | 33134 | 32,000 |
| 90 | Louisville | Kentucky | Yum Brands | Food Services | 40213 | 31,700 |
| 91 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 31,000 |
| 92 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 30,200 |
| 93 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 30,000 |
| 94 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 29,400 |
| 95 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 28,900 |
| 96 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 28,000 |
| 97 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 26,100 |
| 98 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 26,000 |
| 99 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 25,100 |
| 100 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 25,000 |
| 101 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 25,000 |
| 102 | Norwalk | Connecticut | Booking s | Internet Services and Retailing | 06854 | 24,200 |
| 103 | Mountain View | California | Intuit | Computer Software | 94043 | 24,200 |
| 104 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 24,000 |
| 105 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 24,000 |
| 106 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 24,000 |
| 107 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 22,300 |
| 108 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 22,100 |
| 109 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 22,000 |
| 110 | Indianapolis | Indiana | Corteva | Food Production | 46268 | 22,000 |
| 111 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 22,000 |
| 112 | Glen Allen | Virginia | Markel | Insurance: Property and Casualty (Stock) | 23060 | 22,000 |
| 113 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 21,500 |
| 114 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 21,000 |
| 115 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 21,000 |
| 116 | Pleasanton | California | Workday | Computer Software | 94588 | 20,500 |
| 117 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 20,000 |
| 118 | Stamford | Connecticut | Synchrony Financial | Diversified Financials | 06902 | 20,000 |
| 119 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 19,700 |
| 120 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 19,300 |
| 121 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 19,100 |
| 122 | St. Petersburg | Florida | Raymond James Financial | Securities | 33716 | 19,000 |
| 123 | Bellevue | Washington | Expeditors International of Washington | Transportation and Logistics | 98006 | 18,900 |
| 124 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 18,500 |
| 125 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 18,300 |
| 126 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 18,000 |
| 127 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 18,000 |
| 128 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 18,000 |
| 129 | Jacksonville | Florida | GuideWell Mutual | Insurance: Life, Health (Stock) | 32246 | 17,900 |
| 130 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 17,600 |
| 131 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 17,400 |
| 132 | Fremont | California | Lam Research | Semiconductors and Other Electronic Components | 94538 | 17,400 |
| 133 | Raleigh | North Carolina | First Citizens BancShares | Commercial Banks | 27609 | 17,300 |
| 134 | Providence | Rhode Island | Citizens Financial | Commercial Banks | 02903 | 17,300 |
| 135 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 17,000 |
| 136 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 16,800 |
| 137 | Cleveland | Ohio | TransDigm | Aerospace & Defense | 44115 | 16,600 |
| 138 | Seattle | Washington | Expedia | Internet Services and Retailing | 98119 | 16,500 |
| 139 | Columbus | Ohio | American Electric Power | Utilities: Gas and Electric | 43215 | 16,300 |
| 140 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 16,000 |
| 141 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 15,600 |
| 142 | Phoenix | Arizona | Avnet | Wholesalers: Electronics and Office Equipment | 85034 | 15,500 |
| 143 | Lake Forest | Illinois | Packaging Corp. of America | Packaging, Containers | 60045 | 15,400 |
| 144 | Santa Clara | California | Palo Alto Networks | Network and Other Communications Equipment | 95054 | 15,300 |
| 145 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 15,100 |
| 146 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 15,100 |
| 147 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 15,100 |
| 148 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 15,100 |
| 149 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 15,000 |
| 150 | Duluth | Georgia | Asbury Automotive | Automotive Retailing, Services | 30097 | 15,000 |
| 151 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 15,000 |
| 152 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 14,800 |
| 153 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 14,400 |
| 154 | Chandler | Arizona | Insight Enterprises | Information Technology Services | 85286 | 14,300 |
| 155 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 14,200 |
| 156 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 14,000 |
| 157 | Merriam | Kansas | Seaboard | Food Production | 66202 | 14,000 |
| 158 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 14,000 |
| 159 | Los Gatos | California | Netflix | Entertainment | 95032 | 14,000 |
| 160 | Pittsburgh | Pennsylvania | Alcoa | Metals | 15212 | 13,900 |
| 161 | Tampa | Florida | Mosaic | Chemicals | 33602 | 13,800 |
| 162 | Eden Prairie | Minnesota | C.H. Robinson Worldwide | Transportation and Logistics | 55347 | 13,800 |
| 163 | Englewood | Colorado | EchoStar | Telecommunications | 80112 | 13,700 |
| 164 | Redwood City | California | Equinix | Real Estate | 94065 | 13,600 |
| 165 | Newark | New Jersey | Public Service Enterprise | Utilities: Gas and Electric | 07102 | 13,000 |
| 166 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 13,000 |
| 167 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 12,700 |
| 168 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 12,500 |
| 169 | Akron | Ohio | FirstEnergy | Utilities: Gas and Electric | 44308 | 12,300 |
| 170 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 12,300 |
| 171 | Birmingham | Alabama | Vulcan Materials | Building Materials, Glass | 35242 | 12,000 |
| 172 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 11,600 |
| 173 | Oakland | California | Block | Financial Data Services | 94612 | 11,400 |
| 174 | Westchester | Illinois | Ingredion | Food Production | 60154 | 11,200 |
| 175 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 11,100 |
| 176 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 10,900 |
| 177 | Long Island City | New York | Altice USA | Telecommunications | 11101 | 10,900 |
| 178 | Charlotte | North Carolina | Sonic Automotive | Automotive Retailing, Services | 28211 | 10,800 |
| 179 | Springfield | Massachusetts | Eversource Energy | Utilities: Gas and Electric | 01104 | 10,700 |
| 180 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 10,700 |
| 181 | San Mateo | California | Franklin Resources | Securities | 94403 | 10,200 |
| 182 | Beverly Hills | California | Endeavor | Entertainment | 90210 | 10,000 |
| 183 | San Antonio | Texas | Valero Energy | Petroleum Refining | 78249 | 9,900 |
| 184 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 9,900 |
| 185 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 9,800 |
| 186 | Detroit | Michigan | DTE Energy | Utilities: Gas and Electric | 48226 | 9,500 |
| 187 | Chicago | Illinois | Old Republic International | Insurance: Property and Casualty (Stock) | 60601 | 9,400 |
| 188 | Victor | New York | Constellation Brands | Beverages | 14564 | 9,300 |
| 189 | Arlington | Virginia | AES | Utilities: Gas and Electric | 22203 | 9,100 |
| 190 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 9,000 |
| 191 | San Diego | California | LPL Financial s | Securities | 92121 | 9,000 |
| 192 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 9,000 |
| 193 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 8,300 |
| 194 | Washington | District of Columbia | Fannie Mae | Diversified Financials | 20005 | 8,200 |
| 195 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 8,100 |
| 196 | McLean | Virginia | Freddie Mac | Diversified Financials | 22102 | 8,100 |
| 197 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 7,900 |
| 198 | Cambridge | Massachusetts | Biogen | Pharmaceuticals | 02142 | 7,600 |
| 199 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 7,300 |
| 200 | Milwaukee | Wisconsin | WEC Energy | Utilities: Gas and Electric | 53203 | 7,000 |
| 201 | Reston | Virginia | NVR | Homebuilders | 20190 | 7,000 |
| 202 | Atlanta | Georgia | Pulte | Homebuilders | 30326 | 6,800 |
| 203 | Irving | Texas | Vistra | Energy | 75039 | 6,800 |
| 204 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 6,700 |
| 205 | Allentown | Pennsylvania | PPL | Utilities: Gas and Electric | 18101 | 6,700 |
| 206 | Omaha | Nebraska | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | 68175 | 6,500 |
| 207 | Richmond | Virginia | Altria | Tobacco | 23230 | 6,200 |
| 208 | Corona | California | Monster Beverage | Beverages | 92879 | 6,000 |
| 209 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 5,800 |
| 210 | San Jose | California | Super Micro Computer | Computers, Office Equipment | 95131 | 5,700 |
| 211 | St. Louis | Missouri | Core & Main | Wholesalers: Diversified | 63146 | 5,700 |
| 212 | St. Paul | Minnesota | Securian Financial | Insurance: Life, Health (Stock) | 55101 | 5,600 |
| 213 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 5,600 |
| 214 | Dallas | Texas | HF Sinclair | Petroleum Refining | 75219 | 5,300 |
| 215 | Tulsa | Oklahoma | Oneok | Pipelines | 74103 | 5,200 |
| 216 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 4,900 |
| 217 | Miami | Florida | World Kinect | Energy | 33178 | 4,700 |
| 218 | Boston | Massachusetts | American Tower | Real Estate | 02116 | 4,700 |
| 219 | Newport Beach | California | Pacific Life | Insurance: Life, Health (Stock) | 92660 | 4,300 |
| 220 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 4,100 |
| 221 | Minneapolis | Minnesota | Thrivent Financial for Lutherans | Insurance: Life, Health (Mutual) | 55415 | 4,000 |
| 222 | Parsippany | New Jersey | PBF Energy | Petroleum Refining | 07054 | 3,900 |
| 223 | Waltham | Massachusetts | Global Partners | Energy | 02453 | 3,800 |
| 224 | Scottsdale | Arizona | Taylor Morrison Home | Homebuilders | 85251 | 3,000 |
| 225 | Greenwich | Connecticut | Interactive Brokers | Securities | 06830 | 3,000 |
| 226 | San Francisco | California | Prologis | Real Estate | 94111 | 2,700 |
| 227 | Cincinnati | Ohio | Western & Southern Financial | Insurance: Life, Health (Mutual) | 45202 | 2,700 |
| 228 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 2,300 |
| 229 | Maumee | Ohio | Andersons | Food Production | 43537 | 2,300 |
| 230 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 2,000 |
| 231 | Brentwood | Tennessee | Delek US | Petroleum Refining | 37027 | 2,000 |
| 232 | New York | New York | Hess | Mining, Crude-Oil Production | 10036 | 1,800 |
| 233 | Houston | Texas | Cheniere Energy | Pipelines | 77002 | 1,700 |
| 234 | Denver | Colorado | Ovintiv | Mining, Crude-Oil Production | 80202 | 1,600 |
| 235 | Toledo | Ohio | Welltower | Real Estate | 43615 | 700 |
| 236 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 500 |
In [183]:
# Join the Dataframe 'gdfusact' with 'dfminempco' for the Top 10
gdfusactminempco = gdfusact.merge(dfminempco, how = 'inner', on = ['Zip Code'])
gdfusactminempco = gdfusactminempco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [184]:
mctminempco = gdfusactminempco.explore(column='Revenue (rounded)', name='Smallest Employer Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctminempco)
mctminempco
Out[184]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [185]:
# Check the Total Employee in each City
dfctte = df.groupby(['City','State'])[df.columns[[6]]].sum('Employees').sort_values('Employees', ascending=False)
dfctte
Out[185]:
| Employees | ||
|---|---|---|
| City | State | |
| Seattle | Washington | 2101600 |
| Bentonville | Arkansas | 2100000 |
| New York | New York | 2028200 |
| Atlanta | Georgia | 1233700 |
| Chicago | Illinois | 724600 |
| Cincinnati | Ohio | 593500 |
| Dallas | Texas | 590100 |
| Minneapolis | Minnesota | 573300 |
| Memphis | Tennessee | 559900 |
| Houston | Texas | 557600 |
| San Francisco | California | 492000 |
| Omaha | Nebraska | 463100 |
| Newark | California | 450000 |
| Philadelphia | Pennsylvania | 448700 |
| Charlotte | North Carolina | 422700 |
| Eden Prairie | Minnesota | 413800 |
| Arlington | Virginia | 367100 |
| Framingham | Massachusetts | 364000 |
| Purchase | New York | 354300 |
| Teaneck | New Jersey | 336800 |
| Issaquah | Washington | 333000 |
| Deerfield | Illinois | 290500 |
| Irving | Texas | 287000 |
| Austin | Texas | 284700 |
| Armonk | New York | 284500 |
| Bethesda | Maryland | 276000 |
| McLean | Virginia | 275900 |
| Nashville | Tennessee | 271000 |
| Woonsocket | Rhode Island | 259500 |
| Lakeland | Florida | 255000 |
| Santa Clara | California | 250200 |
| San Jose | California | 248200 |
| Plano | Texas | 245500 |
| Boise | Idaho | 244600 |
| Redmond | Washington | 228000 |
| Stamford | Connecticut | 225500 |
| Reston | Virginia | 220000 |
| Mooresville | North Carolina | 215500 |
| Pittsburgh | Pennsylvania | 209800 |
| Mountain View | California | 207500 |
| Burbank | California | 205000 |
| Goodlettsville | Tennessee | 194200 |
| Orlando | Florida | 191100 |
| Cleveland | Ohio | 188400 |
| Detroit | Michigan | 182200 |
| Greenwich | Connecticut | 179600 |
| Southfield | Michigan | 173700 |
| Indianapolis | Indiana | 172700 |
| Dearborn | Michigan | 171000 |
| Cupertino | California | 164000 |
| St. Louis | Missouri | 160700 |
| St. Petersburg | Florida | 157000 |
| Chesapeake | Virginia | 139600 |
| New Brunswick | New Jersey | 138100 |
| Springdale | Arkansas | 138000 |
| Newport Beach | California | 134800 |
| Louisville | Kentucky | 134400 |
| Fort Worth | Texas | 133300 |
| Ashburn | Virginia | 130000 |
| Waltham | Massachusetts | 128800 |
| Wallingford | Connecticut | 125000 |
| Denver | Colorado | 123800 |
| Spring | Texas | 121900 |
| Phoenix | Arizona | 121000 |
| Boston | Massachusetts | 115500 |
| St. Paul | Minnesota | 115100 |
| Jacksonville | Florida | 114900 |
| Abbott Park | Illinois | 114000 |
| Las Vegas | Nevada | 109100 |
| Round Rock | Texas | 108000 |
| Dublin | California | 107000 |
| Milwaukee | Wisconsin | 106900 |
| Auburn Hills | Michigan | 100600 |
| Richmond | Virginia | 99300 |
| Falls Church | Virginia | 97000 |
| Palo Alto | California | 95000 |
| Washington | District of Columbia | 93200 |
| Durham | North Carolina | 88000 |
| King of Prussia | Pennsylvania | 87500 |
| Marlborough | Massachusetts | 86000 |
| Springfield | Missouri | 85600 |
| Richfield | Minnesota | 85000 |
| Cambridge | Massachusetts | 84400 |
| Coral Gables | Florida | 82700 |
| Akron | Ohio | 80300 |
| Providence | Rhode Island | 79600 |
| Beaverton | Oregon | 79400 |
| Newport News | Virginia | 79000 |
| San Diego | California | 74800 |
| Menlo Park | California | 74100 |
| Franklin Lakes | New Jersey | 74000 |
| Rahway | New Jersey | 74000 |
| Bloomfield | Connecticut | 72400 |
| Farmington | Connecticut | 72000 |
| Columbus | Indiana | 69600 |
| Bloomington | Illinois | 67400 |
| Mayfield Village | Ohio | 66300 |
| Burlington | North Carolina | 65400 |
| Raleigh | North Carolina | 65300 |
| Norwalk | Connecticut | 64600 |
| Roseland | New Jersey | 64000 |
| Menomonee Falls | Wisconsin | 60000 |
| Columbus | Ohio | 58700 |
| Corning | New York | 56300 |
| Rolling Meadows | Illinois | 56000 |
| Moline | Illinois | 55500 |
| Northbrook | Illinois | 55200 |
| North Chicago | Illinois | 55000 |
| Des Peres | Missouri | 55000 |
| Portage | Michigan | 53000 |
| Evendale | Ohio | 53000 |
| Franklin | Tennessee | 52500 |
| Newark | New Jersey | 50900 |
| Secaucus | New Jersey | 50500 |
| Reno | Nevada | 50000 |
| Bellevue | Washington | 49000 |
| New Britain | Connecticut | 48500 |
| Dublin | Ohio | 48400 |
| Palm Beach Gardens | Florida | 48000 |
| San Antonio | Texas | 47900 |
| Burlington | New Jersey | 47300 |
| Antioch | Tennessee | 47000 |
| Melbourne | Florida | 47000 |
| Glen Allen | Virginia | 45200 |
| Conshohocken | Pennsylvania | 44000 |
| Benton Harbor | Michigan | 44000 |
| Glenview | Illinois | 44000 |
| Fremont | California | 43200 |
| Evansville | Indiana | 42000 |
| Maumee | Ohio | 41900 |
| Calhoun | Georgia | 41900 |
| Brentwood | Tennessee | 41000 |
| Lake Forest | Illinois | 40400 |
| Oakland | California | 39800 |
| Sumner | Washington | 39000 |
| Duluth | Georgia | 39000 |
| Bolingbrook | Illinois | 39000 |
| Parsippany | New Jersey | 38200 |
| Coraopolis | Pennsylvania | 37400 |
| Tampa | Florida | 36800 |
| Chandler | Arizona | 36600 |
| Midland | Michigan | 36000 |
| Mentor | Ohio | 35000 |
| Beverly Hills | California | 34200 |
| Princeton | New Jersey | 34100 |
| Lowell | Arkansas | 33600 |
| Ankeny | Iowa | 33100 |
| Englewood | Colorado | 32700 |
| Westlake | Texas | 32100 |
| Canonsburg | Pennsylvania | 32000 |
| Birmingham | Alabama | 31600 |
| Westerville | Ohio | 31000 |
| Long Island City | New York | 30700 |
| Medford | Oregon | 30200 |
| Rosemont | Illinois | 30000 |
| Burlington | Massachusetts | 29400 |
| Allentown | Pennsylvania | 29100 |
| Bloomfield Hills | Michigan | 28900 |
| Thousand Oaks | California | 28000 |
| Redwood City | California | 27300 |
| Irvine | California | 26100 |
| Estero | Florida | 26000 |
| Toledo | Ohio | 25700 |
| Miami | Florida | 25300 |
| Fort Lauderdale | Florida | 25100 |
| Melville | New York | 25000 |
| Monroe | Louisiana | 25000 |
| Wilmington | Massachusetts | 24000 |
| Delaware | 24000 | |
| Downers Grove | Illinois | 24000 |
| Elkhart | Indiana | 22300 |
| Buffalo | New York | 22100 |
| Maplewood | Minnesota | 22000 |
| Summit | New Jersey | 22000 |
| Springfield | Massachusetts | 21900 |
| Centennial | Colorado | 21500 |
| Riverwoods | Illinois | 21000 |
| Winona | Minnesota | 21000 |
| Pleasanton | California | 20500 |
| Austin | Minnesota | 20000 |
| Des Moines | Iowa | 19700 |
| Hershey | Pennsylvania | 19300 |
| Hartford | Connecticut | 19100 |
| Scottsdale | Arizona | 19000 |
| Oshkosh | Wisconsin | 18500 |
| Findlay | Ohio | 18300 |
| Livonia | Michigan | 18000 |
| Plantation | Florida | 18000 |
| Long Beach | California | 18000 |
| Foster City | California | 17600 |
| Tempe | Arizona | 17400 |
| Warsaw | Indiana | 17000 |
| Juno Beach | Florida | 16800 |
| Westminster | Colorado | 16000 |
| Sunnyvale | California | 15600 |
| Milpitas | California | 15100 |
| Manhattan Beach | California | 15100 |
| Vernon Hills | Illinois | 15100 |
| Tarrytown | New York | 15100 |
| Sunny Isles Beach | Florida | 15000 |
| Byron Center | Michigan | 15000 |
| Arlington | Texas | 14800 |
| Camden | New Jersey | 14400 |
| Baltimore | Maryland | 14200 |
| Los Gatos | California | 14000 |
| Merriam | Kansas | 14000 |
| Kingsport | Tennessee | 14000 |
| Rosemead | California | 14000 |
| Fort Wayne | Indiana | 13000 |
| Columbus | Georgia | 12700 |
| Oak Brook | Illinois | 12500 |
| New Orleans | Louisiana | 12300 |
| El Dorado | Arkansas | 11600 |
| Westchester | Illinois | 11200 |
| Madison | Wisconsin | 11100 |
| Tulsa | Oklahoma | 11000 |
| Chattanooga | Tennessee | 10900 |
| Inver Grove Heights | Minnesota | 10700 |
| San Mateo | California | 10200 |
| Woodland Hills | California | 9900 |
| Radnor | Pennsylvania | 9800 |
| Victor | New York | 9300 |
| Orrville | Ohio | 9000 |
| Arden Hills | Minnesota | 9000 |
| Jackson | Michigan | 8300 |
| Herndon | Virginia | 8100 |
| New Braunfels | Texas | 7900 |
| Lansing | Michigan | 7300 |
| Erie | Pennsylvania | 6700 |
| Corona | California | 6000 |
| Johnston | Rhode Island | 5800 |
| Fairfield | Ohio | 5600 |
| Fort Washington | Pennsylvania | 4900 |
| Chesterfield | Missouri | 4100 |
| Oklahoma City | Oklahoma | 2300 |
| Midland | Texas | 2000 |
| El Segundo | California | 500 |
In [186]:
# Join the Dataframe 'gdfusact' with 'dfctte' for the Top 10
dfctte = dfctte.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctte = gdfusact.merge(dfctte, how = 'inner', on = ['Zip Code'])
gdfusactctte = gdfusactctte.sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactctte
Out[186]:
| Zip Code | Latitude | Longitude | Population | geometry | City | State | Employees | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Seattle | Washington | 2101600 | Amazon |
| 1 | 98188 | 47 | -122 | 26,769 | POINT (-122.27398 47.44754) | Seattle | Washington | 2101600 | Alaska Air |
| 2 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Seattle | Washington | 2101600 | Nordstrom |
| 3 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Seattle | Washington | 2101600 | Coupang |
| 4 | 98134 | 48 | -122 | 779 | POINT (-122.33686 47.57691) | Seattle | Washington | 2101600 | Starbucks |
| 5 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Seattle | Washington | 2101600 | Expedia |
| 6 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | Bentonville | Arkansas | 2100000 | Walmart |
| 7 | 10041 | 41 | -74 | 6,217 | POINT (-74.01 40.7031) | New York | New York | 2028200 | S&P Global |
| 8 | 10006 | 41 | -74 | 4,475 | POINT (-74.01306 40.70949) | New York | New York | 2028200 | ABM Industries |
| 9 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | Omnicom |
| 10 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | Kyndryl s |
| 11 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | Travelers |
| 12 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | TIAA |
| 13 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | JPMorgan Chase |
| 14 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | New York | 2028200 | Oscar Health |
| 15 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | New York | 2028200 | Citi |
| 16 | 10010 | 41 | -74 | 31,905 | POINT (-73.98243 40.73899) | New York | New York | 2028200 | New York Life Insurance |
| 17 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | New York | 2028200 | Consolidated Edison |
| 18 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | Apollo Global Management |
| 19 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | New York | 2028200 | Warner Bros. Discovery |
| 20 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | Foot Locker |
| 21 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | Guardian Life |
| 22 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | BlackRock |
| 23 | 10105 | 41 | -74 | 0 | POINT (-73.978 40.7644) | New York | New York | 2028200 | Equitable |
| 24 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | New York | New York | 2028200 | Bank of New York |
| 25 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | Macy's |
| 26 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | PVH |
| 27 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | Loews |
| 28 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | New York | New York | 2028200 | Goldman Sachs |
| 29 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Marsh & McLennan |
| 30 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | New York | 2028200 | Voya Financial |
| 31 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | New York | 2028200 | StoneX |
| 32 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | New York | New York | 2028200 | Blackstone |
| 33 | 10153 | 41 | -74 | 0 | POINT (-73.97244 40.76362) | New York | New York | 2028200 | Estée Lauder |
| 34 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | News Corp. |
| 35 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Hess |
| 36 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Fox |
| 37 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Paramount Global |
| 38 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | International Flavors & Fragrances |
| 39 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Morgan Stanley |
| 40 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | Verizon |
| 41 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | Jefferies Financial |
| 42 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | Interpublic |
| 43 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | Colgate-Palmolive |
| 44 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | KKR |
| 45 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | New York | 2028200 | American International |
| 46 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | New York | 2028200 | Sirius XM |
| 47 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | New York | New York | 2028200 | American Express |
| 48 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | Pfizer |
| 49 | 10166 | 41 | -74 | 0 | POINT (-73.9769 40.7531) | New York | New York | 2028200 | MetLife |
| 50 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Atlanta | Georgia | 1233700 | UPS |
| 51 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Atlanta | Georgia | 1233700 | Assurant |
| 52 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Atlanta | Georgia | 1233700 | Genuine Parts |
| 53 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Atlanta | Georgia | 1233700 | Home Depot |
| 54 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Atlanta | Georgia | 1233700 | Newell Brands |
| 55 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Atlanta | Georgia | 1233700 | Graphic Packaging |
| 56 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Atlanta | Georgia | 1233700 | Intercontinental Exchange |
| 57 | 30354 | 34 | -84 | 15,487 | POINT (-84.38609 33.66058) | Atlanta | Georgia | 1233700 | Delta Airlines |
| 58 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Atlanta | Georgia | 1233700 | Global Payments |
| 59 | 30313 | 34 | -84 | 10,845 | POINT (-84.39761 33.76369) | Atlanta | Georgia | 1233700 | Coca-Cola |
| 60 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Atlanta | Georgia | 1233700 | Norfolk Southern |
| 61 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Atlanta | Georgia | 1233700 | Southern |
| 62 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Atlanta | Georgia | 1233700 | Pulte |
| 63 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Chicago | Illinois | 724600 | Exelon |
| 64 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Chicago | Illinois | 724600 | Motorola Solutions |
| 65 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Chicago | Illinois | 724600 | GE HealthCare Technologies |
| 66 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Chicago | Illinois | 724600 | Conagra Brands |
| 67 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Chicago | Illinois | 724600 | Kellanova |
| 68 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Chicago | Illinois | 724600 | McDonald's |
| 69 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Chicago | Illinois | 724600 | Mondelez |
| 70 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Chicago | Illinois | 724600 | Molson Coors Beverage |
| 71 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Chicago | Illinois | 724600 | United Airlines |
| 72 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Chicago | Illinois | 724600 | Northern Trust |
| 73 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Chicago | Illinois | 724600 | Old Republic International |
| 74 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Chicago | Illinois | 724600 | Jones Lang LaSalle |
| 75 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Chicago | Illinois | 724600 | Archer Daniels Midland |
| 76 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Chicago | Illinois | 724600 | Kraft Heinz |
| 77 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Cincinnati | Ohio | 593500 | American Financial |
| 78 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Cincinnati | Ohio | 593500 | Western & Southern Financial |
| 79 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Cincinnati | Ohio | 593500 | Procter & Gamble |
| 80 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Cincinnati | Ohio | 593500 | Kroger |
| 81 | 45262 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Cincinnati | Ohio | 593500 | Cintas |
| 82 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Cincinnati | Ohio | 593500 | Fifth Third Bancorp |
| 83 | 75240 | 33 | -97 | 24,718 | POINT (-96.78924 32.93194) | Dallas | Texas | 590100 | AECOM |
| 84 | 75254 | 33 | -97 | 24,737 | POINT (-96.80127 32.94571) | Dallas | Texas | 590100 | Tenet Healthcare |
| 85 | 75243 | 33 | -97 | 63,907 | POINT (-96.73633 32.91232) | Dallas | Texas | 590100 | Texas Instruments |
| 86 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Dallas | Texas | 590100 | CBRE |
| 87 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Dallas | Texas | 590100 | Jacobs Solutions |
| 88 | 75202 | 33 | -97 | 2,744 | POINT (-96.8037 32.77843) | Dallas | Texas | 590100 | AT&T |
| 89 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Dallas | Texas | 590100 | HF Sinclair |
| 90 | 75225 | 33 | -97 | 22,383 | POINT (-96.79109 32.86511) | Dallas | Texas | 590100 | Energy Transfer |
| 91 | 75235 | 33 | -97 | 19,067 | POINT (-96.84798 32.83219) | Dallas | Texas | 590100 | Southwest Airlines |
| 92 | 55402 | 45 | -93 | 760 | POINT (-93.27119 44.97608) | Minneapolis | Minnesota | 573300 | U.S. Bancorp |
| 93 | 55474 | 45 | -93 | 28,071 | POINT (-93.27 44.98) | Minneapolis | Minnesota | 573300 | Ameriprise Financial |
| 94 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | Minneapolis | Minnesota | 573300 | Target |
| 95 | 55415 | 45 | -93 | 6,474 | POINT (-93.2578 44.97463) | Minneapolis | Minnesota | 573300 | Thrivent Financial for Lutherans |
| 96 | 55426 | 45 | -93 | 25,451 | POINT (-93.38139 44.95635) | Minneapolis | Minnesota | 573300 | General Mills |
| 97 | 55401 | 45 | -93 | 11,526 | POINT (-93.26984 44.98526) | Minneapolis | Minnesota | 573300 | Xcel Energy |
| 98 | 38103 | 35 | -90 | 14,025 | POINT (-90.05518 35.15308) | Memphis | Tennessee | 559900 | AutoZone |
| 99 | 38120 | 35 | -90 | 13,249 | POINT (-89.85237 35.12344) | Memphis | Tennessee | 559900 | FedEx |
| 100 | 38197 | 35 | -90 | 0 | POINT (-90.0487 35.1497) | Memphis | Tennessee | 559900 | International Paper |
| 101 | 77008 | 30 | -95 | 40,155 | POINT (-95.41766 29.79856) | Houston | Texas | 557600 | Quanta Services |
| 102 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | KBR |
| 103 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | CenterPoint Energy |
| 104 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | NRG Energy |
| 105 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Chevron |
| 106 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Cheniere Energy |
| 107 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Targa Resources |
| 108 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Waste Management |
| 109 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | EOG Resources |
| 110 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Plains GP |
| 111 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Kinder Morgan |
| 112 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Houston | Texas | 557600 | Enterprise Products Partners |
| 113 | 77056 | 30 | -95 | 23,314 | POINT (-95.46806 29.74849) | Houston | Texas | 557600 | Westlake |
| 114 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Houston | Texas | 557600 | 1 Automotive |
| 115 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Houston | Texas | 557600 | Par Pacific |
| 116 | 77032 | 30 | -95 | 13,536 | POINT (-95.34004 29.96523) | Houston | Texas | 557600 | Halliburton |
| 117 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Houston | Texas | 557600 | Phillips 66 |
| 118 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Houston | Texas | 557600 | APA |
| 119 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Houston | Texas | 557600 | NOV |
| 120 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Houston | Texas | 557600 | Occidental Petroleum |
| 121 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Houston | Texas | 557600 | Corebridge Financial |
| 122 | 77077 | 30 | -96 | 63,421 | POINT (-95.64189 29.75375) | Houston | Texas | 557600 | Sysco |
| 123 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Houston | Texas | 557600 | ConocoPhillips |
| 124 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Houston | Texas | 557600 | Baker Hughes |
| 125 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | San Francisco | California | 492000 | Uber |
| 126 | 94111 | 38 | -122 | 4,553 | POINT (-122.3998 37.79847) | San Francisco | California | 492000 | Prologis |
| 127 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | San Francisco | California | 492000 | DoorDash |
| 128 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | San Francisco | California | 492000 | Visa |
| 129 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | San Francisco | California | 492000 | Wells Fargo |
| 130 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | San Francisco | California | 492000 | Salesforce |
| 131 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | San Francisco | California | 492000 | Gap |
| 132 | 94109 | 38 | -122 | 54,397 | POINT (-122.42138 37.79334) | San Francisco | California | 492000 | Williams-Sonoma |
| 133 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | San Francisco | California | 492000 | Airbnb |
| 134 | 68179 | 41 | -96 | 0 | POINT (-95.9352 41.2597) | Omaha | Nebraska | 463100 | Union Pacific |
| 135 | 68131 | 41 | -96 | 13,928 | POINT (-95.96479 41.26435) | Omaha | Nebraska | 463100 | Berkshire Hathaway |
| 136 | 68102 | 41 | -96 | 9,311 | POINT (-95.93224 41.26231) | Omaha | Nebraska | 463100 | Peter Kiewit Sons' |
| 137 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | Omaha | Nebraska | 463100 | Mutual of Omaha Insurance |
| 138 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | Newark | California | 450000 | Concentrix |
| 139 | 19103 | 40 | -75 | 25,602 | POINT (-75.17386 39.95303) | Philadelphia | Pennsylvania | 448700 | Comcast |
| 140 | 19103 | 40 | -75 | 25,602 | POINT (-75.17386 39.95303) | Philadelphia | Pennsylvania | 448700 | Aramark |
| 141 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | Charlotte | North Carolina | 422700 | Honeywell |
| 142 | 28255 | 35 | -81 | 0 | POINT (-80.8434 35.2267) | Charlotte | North Carolina | 422700 | Bank of America |
| 143 | 28211 | 35 | -81 | 32,637 | POINT (-80.79604 35.16816) | Charlotte | North Carolina | 422700 | Sonic Automotive |
| 144 | 28211 | 35 | -81 | 32,637 | POINT (-80.79604 35.16816) | Charlotte | North Carolina | 422700 | Nucor |
| 145 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | Charlotte | North Carolina | 422700 | Truist Financial |
| 146 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | Charlotte | North Carolina | 422700 | Duke Energy |
| 147 | 55347 | 45 | -93 | 30,467 | POINT (-93.46638 44.82931) | Eden Prairie | Minnesota | 413800 | C.H. Robinson Worldwide |
| 148 | 55344 | 45 | -93 | 14,180 | POINT (-93.43037 44.86452) | Eden Prairie | Minnesota | 413800 | UnitedHealth |
| 149 | 22209 | 39 | -77 | 13,725 | POINT (-77.07309 38.89413) | Arlington | Virginia | 367100 | RTX |
| 150 | 22203 | 39 | -77 | 25,921 | POINT (-77.1164 38.87377) | Arlington | Virginia | 367100 | AES |
| 151 | 22202 | 39 | -77 | 27,352 | POINT (-77.05175 38.8569) | Arlington | Virginia | 367100 | Boeing |
| 152 | 01701 | 42 | -71 | 32,270 | POINT (-71.43796 42.32195) | Framingham | Massachusetts | 364000 | TJX |
| 153 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | Purchase | New York | 354300 | PepsiCo |
| 154 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | Purchase | New York | 354300 | Mastercard |
| 155 | 07666 | 41 | -74 | 41,499 | POINT (-74.01067 40.88998) | Teaneck | New Jersey | 336800 | Cognizant Technology |
| 156 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | Issaquah | Washington | 333000 | Costco |
| 157 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Deerfield | Illinois | 290500 | Walgreens |
| 158 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Deerfield | Illinois | 290500 | Baxter International |
| 159 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Fluor |
| 160 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | McKesson |
| 161 | 75038 | 33 | -97 | 33,097 | POINT (-96.97946 32.87231) | Irving | Texas | 287000 | Kimberly-Clark |
| 162 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Commercial Metals |
| 163 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Celanese |
| 164 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Caterpillar |
| 165 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Builders FirstSource |
| 166 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Irving | Texas | 287000 | Vistra |
| 167 | 78725 | 30 | -98 | 10,810 | POINT (-97.60859 30.23554) | Austin | Texas | 284700 | Tesla |
| 168 | 78741 | 30 | -98 | 45,274 | POINT (-97.71389 30.23007) | Austin | Texas | 284700 | Oracle |
| 169 | 10504 | 41 | -74 | 7,853 | POINT (-73.70629 41.13065) | Armonk | New York | 284500 | IBM |
| 170 | 20814 | 39 | -77 | 30,822 | POINT (-77.10295 39.00506) | Bethesda | Maryland | 276000 | Marriott International |
| 171 | 20817 | 39 | -77 | 37,738 | POINT (-77.14919 38.99809) | Bethesda | Maryland | 276000 | Lockheed Martin |
| 172 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | McLean | Virginia | 275900 | Capital One |
| 173 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | McLean | Virginia | 275900 | Booz Allen Hamilton |
| 174 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | McLean | Virginia | 275900 | Freddie Mac |
| 175 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | McLean | Virginia | 275900 | Hilton |
| 176 | 37203 | 36 | -87 | 20,234 | POINT (-86.78986 36.14937) | Nashville | Tennessee | 271000 | HCA Healthcare |
| 177 | 02895 | 42 | -71 | 43,081 | POINT (-71.49923 42.00103) | Woonsocket | Rhode Island | 259500 | CVS Health |
| 178 | 33811 | 28 | -82 | 28,456 | POINT (-82.01866 27.97933) | Lakeland | Florida | 255000 | Publix Super Markets |
| 179 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | Santa Clara | California | 250200 | Applied Materials |
| 180 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | Santa Clara | California | 250200 | Intel |
| 181 | 95051 | 37 | -122 | 61,345 | POINT (-121.98444 37.3483) | Santa Clara | California | 250200 | Nvidia |
| 182 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | Santa Clara | California | 250200 | Advanced Micro Devices |
| 183 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | Santa Clara | California | 250200 | Palo Alto Networks |
| 184 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | Santa Clara | California | 250200 | ServiceNow |
| 185 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | San Jose | California | 248200 | Super Micro Computer |
| 186 | 95110 | 37 | -122 | 19,444 | POINT (-121.9097 37.34656) | San Jose | California | 248200 | Adobe |
| 187 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | San Jose | California | 248200 | PayPal |
| 188 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | San Jose | California | 248200 | Sanmina |
| 189 | 95119 | 37 | -122 | 10,449 | POINT (-121.79077 37.22756) | San Jose | California | 248200 | Western Digital |
| 190 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | San Jose | California | 248200 | Cisco Systems |
| 191 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | San Jose | California | 248200 | Ebay |
| 192 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | Plano | Texas | 245500 | Yum China s |
| 193 | 83706 | 44 | -116 | 36,183 | POINT (-116.19427 43.59108) | Boise | Idaho | 244600 | Albertsons |
| 194 | 83716 | 44 | -116 | 21,091 | POINT (-115.6548 43.67271) | Boise | Idaho | 244600 | Micron Technology |
| 195 | 98052 | 48 | -122 | 79,074 | POINT (-122.1203 47.68148) | Redmond | Washington | 228000 | Microsoft |
| 196 | 06901 | 41 | -74 | 10,506 | POINT (-73.53845 41.05349) | Stamford | Connecticut | 225500 | Philip Morris |
| 197 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Stamford | Connecticut | 225500 | Synchrony Financial |
| 198 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Stamford | Connecticut | 225500 | United Rentals |
| 199 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Stamford | Connecticut | 225500 | Charter Communications |
| 200 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Reston | Virginia | 220000 | NVR |
| 201 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Reston | Virginia | 220000 | Leidos s |
| 202 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Reston | Virginia | 220000 | General Dynamics |
| 203 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Reston | Virginia | 220000 | CACI International |
| 204 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Reston | Virginia | 220000 | Science Applications International |
| 205 | 28117 | 36 | -81 | 48,170 | POINT (-80.89658 35.57405) | Mooresville | North Carolina | 215500 | Lowe's |
| 206 | 15222 | 40 | -80 | 5,649 | POINT (-79.9912 40.44998) | Pittsburgh | Pennsylvania | 209800 | PNC |
| 207 | 15219 | 40 | -80 | 11,010 | POINT (-79.98443 40.44304) | Pittsburgh | Pennsylvania | 209800 | United States Steel |
| 208 | 15219 | 40 | -80 | 11,010 | POINT (-79.98443 40.44304) | Pittsburgh | Pennsylvania | 209800 | WESCO International |
| 209 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pittsburgh | Pennsylvania | 209800 | Howmet Aerospace |
| 210 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pittsburgh | Pennsylvania | 209800 | Westinghouse Air Brake Technologies |
| 211 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pittsburgh | Pennsylvania | 209800 | Alcoa |
| 212 | 15272 | 40 | -80 | 2,481 | POINT (-80.0048 40.44246) | Pittsburgh | Pennsylvania | 209800 | PPG Industries |
| 213 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | Mountain View | California | 207500 | Intuit |
| 214 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | Mountain View | California | 207500 | Alphabet |
| 215 | 91521 | 34 | -118 | 11,049 | POINT (-118.3252 34.1569) | Burbank | California | 205000 | Walt Disney |
| 216 | 37072 | 36 | -87 | 32,344 | POINT (-86.74494 36.35686) | Goodlettsville | Tennessee | 194200 | Dollar General |
| 217 | 32837 | 28 | -81 | 49,889 | POINT (-81.41998 28.38074) | Orlando | Florida | 191100 | Darden Restaurants |
| 218 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Cleveland | Ohio | 188400 | TransDigm |
| 219 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Cleveland | Ohio | 188400 | Sherwin-Williams |
| 220 | 44124 | 41 | -81 | 40,046 | POINT (-81.46774 41.49999) | Cleveland | Ohio | 188400 | Parker-Hannifin |
| 221 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Cleveland | Ohio | 188400 | KeyCorp |
| 222 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Cleveland | Ohio | 188400 | Cleveland-Cliffs |
| 223 | 48265 | 42 | -83 | 4,503 | POINT (-83.0456 42.3317) | Detroit | Michigan | 182200 | General Motors |
| 224 | 48226 | 42 | -83 | 6,893 | POINT (-83.05034 42.33182) | Detroit | Michigan | 182200 | DTE Energy |
| 225 | 48226 | 42 | -83 | 6,893 | POINT (-83.05034 42.33182) | Detroit | Michigan | 182200 | Ally Financial |
| 226 | 06831 | 41 | -74 | 14,656 | POINT (-73.66078 41.08782) | Greenwich | Connecticut | 179600 | GXO Logistics |
| 227 | 06831 | 41 | -74 | 14,656 | POINT (-73.66078 41.08782) | Greenwich | Connecticut | 179600 | XPO |
| 228 | 06830 | 41 | -74 | 24,919 | POINT (-73.624 41.048) | Greenwich | Connecticut | 179600 | W.R. Berkley |
| 229 | 06830 | 41 | -74 | 24,919 | POINT (-73.624 41.048) | Greenwich | Connecticut | 179600 | Interactive Brokers |
| 230 | 48033 | 42 | -83 | 16,900 | POINT (-83.28812 42.46478) | Southfield | Michigan | 173700 | Lear |
| 231 | 46204 | 40 | -86 | 11,022 | POINT (-86.15703 39.77134) | Indianapolis | Indiana | 172700 | Elevance Health |
| 232 | 46285 | 40 | -86 | 0 | POINT (-86.1582 39.7683) | Indianapolis | Indiana | 172700 | Eli Lilly |
| 233 | 46268 | 40 | -86 | 25,623 | POINT (-86.23253 39.89769) | Indianapolis | Indiana | 172700 | Corteva |
| 234 | 48126 | 42 | -83 | 52,075 | POINT (-83.18678 42.32999) | Dearborn | Michigan | 171000 | Ford Motor |
| 235 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | Cupertino | California | 164000 | Apple |
| 236 | 63144 | 39 | -90 | 9,580 | POINT (-90.3482 38.61943) | St. Louis | Missouri | 160700 | Post s |
| 237 | 63136 | 39 | -90 | 41,314 | POINT (-90.25979 38.74418) | St. Louis | Missouri | 160700 | Emerson Electric |
| 238 | 63105 | 39 | -90 | 18,860 | POINT (-90.32812 38.64427) | St. Louis | Missouri | 160700 | Graybar Electric |
| 239 | 63105 | 39 | -90 | 18,860 | POINT (-90.32812 38.64427) | St. Louis | Missouri | 160700 | Centene |
| 240 | 63146 | 39 | -90 | 30,917 | POINT (-90.47634 38.70135) | St. Louis | Missouri | 160700 | Core & Main |
| 241 | 33716 | 28 | -83 | 18,995 | POINT (-82.65119 27.8774) | St. Petersburg | Florida | 157000 | Raymond James Financial |
| 242 | 33716 | 28 | -83 | 18,995 | POINT (-82.65119 27.8774) | St. Petersburg | Florida | 157000 | Jabil |
| 243 | 23320 | 37 | -76 | 59,626 | POINT (-76.21807 36.75208) | Chesapeake | Virginia | 139600 | Dollar Tree |
| 244 | 72762 | 36 | -94 | 47,402 | POINT (-94.22794 36.18747) | Springdale | Arkansas | 138000 | Tyson Foods |
| 245 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | Newport Beach | California | 134800 | Chipotle Mexican Grill |
| 246 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | Newport Beach | California | 134800 | Pacific Life |
| 247 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | Louisville | Kentucky | 134400 | Yum Brands |
| 248 | 40222 | 38 | -86 | 21,634 | POINT (-85.61173 38.26436) | Louisville | Kentucky | 134400 | BrightSpring Health Services |
| 249 | 40202 | 38 | -86 | 7,109 | POINT (-85.75205 38.25288) | Louisville | Kentucky | 134400 | Humana |
| 250 | 76155 | 33 | -97 | 6,301 | POINT (-97.04911 32.82404) | Fort Worth | Texas | 133300 | American Airlines |
| 251 | 20147 | 39 | -77 | 67,007 | POINT (-77.47958 39.04151) | Ashburn | Virginia | 130000 | DXC Technology |
| 252 | 02453 | 42 | -71 | 30,314 | POINT (-71.24101 42.36918) | Waltham | Massachusetts | 128800 | Global Partners |
| 253 | 02451 | 42 | -71 | 18,153 | POINT (-71.2573 42.39859) | Waltham | Massachusetts | 128800 | Thermo Fisher Scientific |
| 254 | 06492 | 41 | -73 | 44,099 | POINT (-72.80473 41.45927) | Wallingford | Connecticut | 125000 | Amphenol |
| 255 | 80202 | 40 | -105 | 18,233 | POINT (-104.99768 39.75156) | Denver | Colorado | 123800 | VF |
| 256 | 80202 | 40 | -105 | 18,233 | POINT (-104.99768 39.75156) | Denver | Colorado | 123800 | Ovintiv |
| 257 | 80202 | 40 | -105 | 18,233 | POINT (-104.99768 39.75156) | Denver | Colorado | 123800 | DaVita |
| 258 | 80237 | 40 | -105 | 22,764 | POINT (-104.90178 39.63996) | Denver | Colorado | 123800 | Newmont |
| 259 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Spring | Texas | 121900 | Exxon Mobil |
| 260 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Spring | Texas | 121900 | Hewlett Packard |
| 261 | 85054 | 34 | -112 | 10,159 | POINT (-111.94763 33.67515) | Phoenix | Arizona | 121000 | Sprouts Farmers Market |
| 262 | 85054 | 34 | -112 | 10,159 | POINT (-111.94763 33.67515) | Phoenix | Arizona | 121000 | Republic Services |
| 263 | 85034 | 33 | -112 | 4,825 | POINT (-112.01989 33.43465) | Phoenix | Arizona | 121000 | Avnet |
| 264 | 85004 | 33 | -112 | 11,178 | POINT (-112.06988 33.45159) | Phoenix | Arizona | 121000 | Freeport-McMoRan |
| 265 | 02114 | 42 | -71 | 13,853 | POINT (-71.06686 42.36337) | Boston | Massachusetts | 115500 | State Street |
| 266 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Boston | Massachusetts | 115500 | American Tower |
| 267 | 02210 | 42 | -71 | 6,554 | POINT (-71.03942 42.34815) | Boston | Massachusetts | 115500 | Vertex Pharmaceuticals |
| 268 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Boston | Massachusetts | 115500 | Liberty Mutual Insurance |
| 269 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Boston | Massachusetts | 115500 | Wayfair |
| 270 | 55102 | 45 | -93 | 19,565 | POINT (-93.12149 44.93216) | St. Paul | Minnesota | 115100 | Ecolab |
| 271 | 55101 | 45 | -93 | 7,937 | POINT (-93.08739 44.95111) | St. Paul | Minnesota | 115100 | Securian Financial |
| 272 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | St. Paul | Minnesota | 115100 | 3M |
| 273 | 32202 | 30 | -82 | 6,550 | POINT (-81.64786 30.32505) | Jacksonville | Florida | 114900 | Fidelity National Information |
| 274 | 32202 | 30 | -82 | 6,550 | POINT (-81.64786 30.32505) | Jacksonville | Florida | 114900 | CSX |
| 275 | 32204 | 30 | -82 | 8,421 | POINT (-81.68095 30.31636) | Jacksonville | Florida | 114900 | Fidelity National Financial |
| 276 | 32246 | 30 | -82 | 60,443 | POINT (-81.51782 30.29422) | Jacksonville | Florida | 114900 | GuideWell Mutual |
| 277 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | Abbott Park | Illinois | 114000 | Abbott Laboratories |
| 278 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | Las Vegas | Nevada | 109100 | Las Vegas Sands |
| 279 | 89109 | 36 | -115 | 6,924 | POINT (-115.16327 36.12603) | Las Vegas | Nevada | 109100 | MGM Resorts International |
| 280 | 78682 | 30 | -98 | 0 | POINT (-97.7273 30.4076) | Round Rock | Texas | 108000 | Dell Technologies |
| 281 | 94568 | 38 | -122 | 70,542 | POINT (-121.90113 37.71596) | Dublin | California | 107000 | Ross Stores |
| 282 | 53204 | 43 | -88 | 40,008 | POINT (-87.92552 43.01806) | Milwaukee | Wisconsin | 106900 | Rockwell Automation |
| 283 | 53202 | 43 | -88 | 26,269 | POINT (-87.89893 43.04561) | Milwaukee | Wisconsin | 106900 | Northwestern Mutual |
| 284 | 53203 | 43 | -88 | 2,077 | POINT (-87.91603 43.03828) | Milwaukee | Wisconsin | 106900 | Fiserv |
| 285 | 53203 | 43 | -88 | 2,077 | POINT (-87.91603 43.03828) | Milwaukee | Wisconsin | 106900 | WEC Energy |
| 286 | 53212 | 43 | -88 | 29,099 | POINT (-87.90845 43.07464) | Milwaukee | Wisconsin | 106900 | Manpower |
| 287 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | Auburn Hills | Michigan | 100600 | Autoliv |
| 288 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | Auburn Hills | Michigan | 100600 | BorgWarner |
| 289 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Richmond | Virginia | 99300 | Performance Food |
| 290 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Richmond | Virginia | 99300 | CarMax |
| 291 | 23227 | 38 | -77 | 25,574 | POINT (-77.44234 37.61486) | Richmond | Virginia | 99300 | ARKO |
| 292 | 23230 | 38 | -77 | 8,304 | POINT (-77.49153 37.587) | Richmond | Virginia | 99300 | Altria |
| 293 | 23219 | 38 | -77 | 3,856 | POINT (-77.43484 37.54076) | Richmond | Virginia | 99300 | Dominion Energy |
| 294 | 22042 | 39 | -77 | 34,631 | POINT (-77.19406 38.86463) | Falls Church | Virginia | 97000 | Northrop Grumman |
| 295 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | Palo Alto | California | 95000 | HP |
| 296 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | Palo Alto | California | 95000 | Broadcom |
| 297 | 20037 | 39 | -77 | 12,441 | POINT (-77.0535 38.89213) | Washington | District of Columbia | 93200 | Danaher |
| 298 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | Washington | District of Columbia | 93200 | Fannie Mae |
| 299 | 20003 | 39 | -77 | 36,194 | POINT (-76.99033 38.88193) | Washington | District of Columbia | 93200 | Xylem |
| 300 | 27703 | 36 | -79 | 62,994 | POINT (-78.80452 35.96299) | Durham | North Carolina | 88000 | IQVIA s |
| 301 | 19406 | 40 | -75 | 29,388 | POINT (-75.38402 40.09467) | King of Prussia | Pennsylvania | 87500 | Universal Health Services |
| 302 | 01752 | 42 | -72 | 41,398 | POINT (-71.54681 42.3494) | Marlborough | Massachusetts | 86000 | BJ's Wholesale Club |
| 303 | 01752 | 42 | -72 | 41,398 | POINT (-71.54681 42.3494) | Marlborough | Massachusetts | 86000 | Boston Scientific |
| 304 | 65802 | 37 | -93 | 46,005 | POINT (-93.35167 37.21048) | Springfield | Missouri | 85600 | O'Reilly Automotive |
| 305 | 55423 | 45 | -93 | 36,779 | POINT (-93.28144 44.87663) | Richfield | Minnesota | 85000 | Best Buy |
| 306 | 02141 | 42 | -71 | 14,677 | POINT (-71.08218 42.37041) | Cambridge | Massachusetts | 84400 | GE Vernova |
| 307 | 02142 | 42 | -71 | 4,349 | POINT (-71.08189 42.36295) | Cambridge | Massachusetts | 84400 | Biogen |
| 308 | 33134 | 26 | -80 | 36,937 | POINT (-80.2712 25.75338) | Coral Gables | Florida | 82700 | MasTec |
| 309 | 33134 | 26 | -80 | 36,937 | POINT (-80.2712 25.75338) | Coral Gables | Florida | 82700 | Ryder System |
| 310 | 44316 | 41 | -81 | 0 | POINT (-81.47083 41.07854) | Akron | Ohio | 80300 | Goodyear Tire & Rubber |
| 311 | 44308 | 41 | -82 | 1,261 | POINT (-81.51751 41.0818) | Akron | Ohio | 80300 | FirstEnergy |
| 312 | 02908 | 42 | -71 | 39,661 | POINT (-71.43926 41.83877) | Providence | Rhode Island | 79600 | United Natural Foods |
| 313 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Providence | Rhode Island | 79600 | Citizens Financial |
| 314 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Providence | Rhode Island | 79600 | Textron |
| 315 | 97005 | 45 | -123 | 27,812 | POINT (-122.80397 45.49144) | Beaverton | Oregon | 79400 | Nike |
| 316 | 23606 | 37 | -76 | 29,899 | POINT (-76.49557 37.07847) | Newport News | Virginia | 79000 | Ferguson |
| 317 | 23607 | 37 | -76 | 23,028 | POINT (-76.42235 36.98753) | Newport News | Virginia | 79000 | Huntington Ingalls Industries |
| 318 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | San Diego | California | 74800 | Qualcomm |
| 319 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | San Diego | California | 74800 | LPL Financial s |
| 320 | 92101 | 33 | -117 | 48,163 | POINT (-117.18589 32.7162) | San Diego | California | 74800 | Sempra |
| 321 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | Menlo Park | California | 74100 | Meta |
| 322 | 07417 | 41 | -74 | 11,035 | POINT (-74.20836 41.00859) | Franklin Lakes | New Jersey | 74000 | Becton Dickinson |
| 323 | 07065 | 41 | -74 | 29,748 | POINT (-74.28066 40.60765) | Rahway | New Jersey | 74000 | Merck |
| 324 | 06002 | 42 | -73 | 21,547 | POINT (-72.73714 41.84286) | Bloomfield | Connecticut | 72400 | Cigna |
| 325 | 06032 | 42 | -73 | 18,642 | POINT (-72.83147 41.72528) | Farmington | Connecticut | 72000 | Otis Worldwide |
| 326 | 47201 | 39 | -86 | 48,602 | POINT (-85.99432 39.15074) | Columbus | Indiana | 69600 | Cummins |
| 327 | 61710 | 41 | -89 | 79,633 | POINT (-88.9894 40.516) | Bloomington | Illinois | 67400 | State Farm |
| 328 | 44143 | 42 | -81 | 24,337 | POINT (-81.47513 41.55358) | Mayfield Village | Ohio | 66300 | Progressive |
| 329 | 27215 | 36 | -79 | 45,967 | POINT (-79.48729 36.03055) | Burlington | North Carolina | 65400 | Labcorp s |
| 330 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | Raleigh | North Carolina | 65300 | First Citizens BancShares |
| 331 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | Raleigh | North Carolina | 65300 | Advance Auto Parts |
| 332 | 06851 | 41 | -73 | 28,591 | POINT (-73.40387 41.13948) | Norwalk | Connecticut | 64600 | EMCOR |
| 333 | 06854 | 41 | -73 | 31,753 | POINT (-73.42972 41.09148) | Norwalk | Connecticut | 64600 | Booking s |
| 334 | 07068 | 41 | -74 | 6,211 | POINT (-74.30862 40.82077) | Roseland | New Jersey | 64000 | Automatic Data Processing |
| 335 | 53051 | 43 | -88 | 39,000 | POINT (-88.12348 43.14905) | Menomonee Falls | Wisconsin | 60000 | Kohl's |
| 336 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Columbus | Ohio | 58700 | Huntington Bancshares |
| 337 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Columbus | Ohio | 58700 | American Electric Power |
| 338 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Columbus | Ohio | 58700 | Nationwide |
| 339 | 14831 | 42 | -77 | 5,986 | POINT (-77.0553 42.1429) | Corning | New York | 56300 | Corning |
| 340 | 60008 | 42 | -88 | 22,949 | POINT (-88.0229 42.0739) | Rolling Meadows | Illinois | 56000 | Arthur J. Gallagher |
| 341 | 61265 | 41 | -90 | 43,851 | POINT (-90.48895 41.48195) | Moline | Illinois | 55500 | Deere |
| 342 | 60062 | 42 | -88 | 41,667 | POINT (-87.84235 42.12663) | Northbrook | Illinois | 55200 | Allstate |
| 343 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | North Chicago | Illinois | 55000 | AbbVie |
| 344 | 63131 | 39 | -90 | 17,993 | POINT (-90.44365 38.6172) | Des Peres | Missouri | 55000 | Edward Jones |
| 345 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | Evendale | Ohio | 53000 | General Electric |
| 346 | 49002 | 42 | -86 | 19,444 | POINT (-85.55906 42.19867) | Portage | Michigan | 53000 | Stryker |
| 347 | 37067 | 36 | -87 | 31,550 | POINT (-86.77461 35.91314) | Franklin | Tennessee | 52500 | Community Health Systems |
| 348 | 07102 | 41 | -74 | 12,954 | POINT (-74.17343 40.73576) | Newark | New Jersey | 50900 | Public Service Enterprise |
| 349 | 07102 | 41 | -74 | 12,954 | POINT (-74.17343 40.73576) | Newark | New Jersey | 50900 | Prudential Financial |
| 350 | 07094 | 41 | -74 | 21,437 | POINT (-74.06588 40.78109) | Secaucus | New Jersey | 50500 | Quest Diagnostics |
| 351 | 89501 | 40 | -120 | 3,641 | POINT (-119.81262 39.52602) | Reno | Nevada | 50000 | Caesars Entertainment |
| 352 | 98006 | 48 | -122 | 40,770 | POINT (-122.14957 47.55772) | Bellevue | Washington | 49000 | Expeditors International of Washington |
| 353 | 98004 | 48 | -122 | 39,435 | POINT (-122.20548 47.61865) | Bellevue | Washington | 49000 | Paccar |
| 354 | 06053 | 42 | -73 | 35,697 | POINT (-72.7941 41.68874) | New Britain | Connecticut | 48500 | Stanley Black & Decker |
| 355 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Dublin | Ohio | 48400 | Cardinal Health |
| 356 | 33418 | 27 | -80 | 42,979 | POINT (-80.16641 26.86077) | Palm Beach Gardens | Florida | 48000 | Carrier Global |
| 357 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | San Antonio | Texas | 47900 | USAA |
| 358 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | San Antonio | Texas | 47900 | Valero Energy |
| 359 | 08016 | 40 | -75 | 34,801 | POINT (-74.83198 40.06926) | Burlington | New Jersey | 47300 | Burlington Stores |
| 360 | 32919 | 28 | -81 | 0 | POINT (-80.6386 28.0909) | Melbourne | Florida | 47000 | L3Harris Technologies |
| 361 | 37013 | 36 | -87 | 102,055 | POINT (-86.63445 36.04658) | Antioch | Tennessee | 47000 | LKQ |
| 362 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Glen Allen | Virginia | 45200 | Owens & Minor |
| 363 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Glen Allen | Virginia | 45200 | Markel |
| 364 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Conshohocken | Pennsylvania | 44000 | Cencora |
| 365 | 60025 | 42 | -88 | 40,877 | POINT (-87.81204 42.07466) | Glenview | Illinois | 44000 | Illinois Tool Works |
| 366 | 49022 | 42 | -86 | 29,796 | POINT (-86.3675 42.11434) | Benton Harbor | Michigan | 44000 | Whirlpool |
| 367 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | Fremont | California | 43200 | TD Synnex |
| 368 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | Fremont | California | 43200 | Lam Research |
| 369 | 47710 | 38 | -88 | 18,802 | POINT (-87.57618 38.02518) | Evansville | Indiana | 42000 | Berry Global |
| 370 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Maumee | Ohio | 41900 | Andersons |
| 371 | 30701 | 34 | -85 | 43,078 | POINT (-84.95385 34.49535) | Calhoun | Georgia | 41900 | Mohawk Industries |
| 372 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Maumee | Ohio | 41900 | Dana |
| 373 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | Brentwood | Tennessee | 41000 | Tractor Supply |
| 374 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | Brentwood | Tennessee | 41000 | Delek US |
| 375 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Lake Forest | Illinois | 40400 | Packaging Corp. of America |
| 376 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Lake Forest | Illinois | 40400 | W.W. Grainger |
| 377 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | Oakland | California | 39800 | Block |
| 378 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | Oakland | California | 39800 | PG&E |
| 379 | 60440 | 42 | -88 | 52,074 | POINT (-88.07572 41.70125) | Bolingbrook | Illinois | 39000 | Ulta Beauty |
| 380 | 30097 | 34 | -84 | 45,543 | POINT (-84.14702 34.0271) | Duluth | Georgia | 39000 | Asbury Automotive |
| 381 | 30096 | 34 | -84 | 71,141 | POINT (-84.14791 33.97691) | Duluth | Georgia | 39000 | AGCO |
| 382 | 98390 | 47 | -122 | 11,497 | POINT (-122.22894 47.21195) | Sumner | Washington | 39000 | Lululemon athletica |
| 383 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | Parsippany | New Jersey | 38200 | PBF Energy |
| 384 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | Parsippany | New Jersey | 38200 | Zoetis |
| 385 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | Parsippany | New Jersey | 38200 | Avis Budget |
| 386 | 15108 | 41 | -80 | 42,782 | POINT (-80.20031 40.50006) | Coraopolis | Pennsylvania | 37400 | Dick's Sporting Goods |
| 387 | 33637 | 28 | -82 | 17,785 | POINT (-82.36118 28.04715) | Tampa | Florida | 36800 | Crown s |
| 388 | 33602 | 28 | -82 | 19,694 | POINT (-82.45675 27.95371) | Tampa | Florida | 36800 | Mosaic |
| 389 | 85224 | 33 | -112 | 48,304 | POINT (-111.87616 33.32351) | Chandler | Arizona | 36600 | Microchip Technology |
| 390 | 85286 | 33 | -112 | 49,870 | POINT (-111.83156 33.27146) | Chandler | Arizona | 36600 | Insight Enterprises |
| 391 | 48674 | 44 | -84 | 42,547 | POINT (-84.23229 43.70732) | Midland | Michigan | 36000 | Dow |
| 392 | 44060 | 42 | -81 | 60,257 | POINT (-81.32806 41.67742) | Mentor | Ohio | 35000 | Avery Dennison |
| 393 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | Beverly Hills | California | 34200 | Endeavor |
| 394 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | Beverly Hills | California | 34200 | Live Nation Entertainment |
| 395 | 08543 | 40 | -75 | 30,681 | POINT (-74.65804 40.34899) | Princeton | New Jersey | 34100 | Bristol-Myers Squibb |
| 396 | 72745 | 36 | -94 | 14,521 | POINT (-94.10046 36.2477) | Lowell | Arkansas | 33600 | J.B. Hunt Transport Services |
| 397 | 50021 | 42 | -94 | 29,718 | POINT (-93.56838 41.7207) | Ankeny | Iowa | 33100 | Casey's General Stores |
| 398 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Englewood | Colorado | 32700 | EchoStar |
| 399 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Englewood | Colorado | 32700 | QVC |
| 400 | 76262 | 33 | -97 | 43,589 | POINT (-97.22101 33.01137) | Westlake | Texas | 32100 | Charles Schwab |
| 401 | 15317 | 40 | -80 | 43,813 | POINT (-80.16535 40.27105) | Canonsburg | Pennsylvania | 32000 | Viatris |
| 402 | 35203 | 34 | -87 | 3,301 | POINT (-86.80999 33.51847) | Birmingham | Alabama | 31600 | Regions Financial |
| 403 | 35242 | 33 | -87 | 56,956 | POINT (-86.67073 33.42371) | Birmingham | Alabama | 31600 | Vulcan Materials |
| 404 | 43082 | 40 | -83 | 33,799 | POINT (-82.88437 40.15537) | Westerville | Ohio | 31000 | Vertiv s |
| 405 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | Long Island City | New York | 30700 | JetBlue Airways |
| 406 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | Long Island City | New York | 30700 | Altice USA |
| 407 | 97501 | 42 | -123 | 45,008 | POINT (-122.89459 42.2856) | Medford | Oregon | 30200 | Lithia Motors |
| 408 | 60018 | 42 | -88 | 29,302 | POINT (-87.89846 41.99629) | Rosemont | Illinois | 30000 | US Foods |
| 409 | 01803 | 43 | -71 | 26,068 | POINT (-71.20147 42.5028) | Burlington | Massachusetts | 29400 | Keurig Dr Pepper |
| 410 | 18106 | 41 | -76 | 6,437 | POINT (-75.59542 40.57472) | Allentown | Pennsylvania | 29100 | Air Products & Chemicals |
| 411 | 18101 | 41 | -75 | 5,789 | POINT (-75.4698 40.60301) | Allentown | Pennsylvania | 29100 | PPL |
| 412 | 48302 | 43 | -83 | 17,346 | POINT (-83.29608 42.5849) | Bloomfield Hills | Michigan | 28900 | Penske Automotive |
| 413 | 91320 | 34 | -119 | 43,628 | POINT (-118.94795 34.17339) | Thousand Oaks | California | 28000 | Amgen |
| 414 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | Redwood City | California | 27300 | Electronic Arts |
| 415 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | Redwood City | California | 27300 | Equinix |
| 416 | 92612 | 34 | -118 | 33,706 | POINT (-117.82457 33.65984) | Irvine | California | 26100 | Ingram Micro |
| 417 | 33928 | 26 | -82 | 30,786 | POINT (-81.71002 26.43545) | Estero | Florida | 26000 | Hertz |
| 418 | 43659 | 42 | -84 | 0 | POINT (-83.5554 41.6639) | Toledo | Ohio | 25700 | Owens Corning |
| 419 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | Toledo | Ohio | 25700 | Welltower |
| 420 | 33178 | 26 | -80 | 65,515 | POINT (-80.4213 25.83578) | Miami | Florida | 25300 | World Kinect |
| 421 | 33126 | 26 | -80 | 47,038 | POINT (-80.30054 25.78061) | Miami | Florida | 25300 | Lennar |
| 422 | 33133 | 26 | -80 | 34,651 | POINT (-80.24327 25.72983) | Miami | Florida | 25300 | Watsco |
| 423 | 33301 | 26 | -80 | 17,831 | POINT (-80.12745 26.12128) | Fort Lauderdale | Florida | 25100 | AutoNation |
| 424 | 11747 | 41 | -73 | 19,826 | POINT (-73.40931 40.78372) | Melville | New York | 25000 | Henry Schein |
| 425 | 71203 | 33 | -92 | 38,770 | POINT (-92.01351 32.58398) | Monroe | Louisiana | 25000 | Lumen Technologies |
| 426 | 19805 | 40 | -76 | 40,315 | POINT (-75.59373 39.74523) | Wilmington | Delaware | 24000 | DuPont |
| 427 | 60515 | 42 | -88 | 29,045 | POINT (-88.0247 41.80991) | Downers Grove | Illinois | 24000 | Dover |
| 428 | 01887 | 43 | -71 | 23,195 | POINT (-71.16541 42.56091) | Wilmington | Massachusetts | 24000 | Analog Devices |
| 429 | 46514 | 42 | -86 | 41,480 | POINT (-85.97547 41.72328) | Elkhart | Indiana | 22300 | THOR Industries |
| 430 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | Buffalo | New York | 22100 | M&T Bank |
| 431 | 07901 | 41 | -74 | 24,502 | POINT (-74.36604 40.71462) | Summit | New Jersey | 22000 | Kenvue |
| 432 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | Maplewood | Minnesota | 22000 | Solventum |
| 433 | 01111 | 42 | -73 | 0 | POINT (-72.54793 42.11733) | Springfield | Massachusetts | 21900 | Mass Mutual |
| 434 | 01104 | 42 | -73 | 21,745 | POINT (-72.56733 42.13326) | Springfield | Massachusetts | 21900 | Eversource Energy |
| 435 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Centennial | Colorado | 21500 | Arrow Electronics |
| 436 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Riverwoods | Illinois | 21000 | Discover Financial |
| 437 | 55987 | 44 | -92 | 33,911 | POINT (-91.63143 43.98469) | Winona | Minnesota | 21000 | Fastenal |
| 438 | 94588 | 38 | -122 | 34,423 | POINT (-121.88178 37.73801) | Pleasanton | California | 20500 | Workday |
| 439 | 55912 | 44 | -93 | 29,438 | POINT (-92.99148 43.6827) | Austin | Minnesota | 20000 | Hormel Foods |
| 440 | 50392 | 42 | -94 | 15,018 | POINT (-93.628 41.5898) | Des Moines | Iowa | 19700 | Principal Financial |
| 441 | 17033 | 40 | -77 | 17,009 | POINT (-76.62754 40.26829) | Hershey | Pennsylvania | 19300 | Hershey |
| 442 | 06155 | 42 | -73 | 121,054 | POINT (-72.6859 41.7638) | Hartford | Connecticut | 19100 | Hartford Insurance |
| 443 | 85251 | 33 | -112 | 39,976 | POINT (-111.92025 33.49406) | Scottsdale | Arizona | 19000 | Taylor Morrison Home |
| 444 | 85254 | 34 | -112 | 46,655 | POINT (-111.95176 33.61474) | Scottsdale | Arizona | 19000 | Reliance |
| 445 | 54902 | 44 | -89 | 21,982 | POINT (-88.53969 43.94934) | Oshkosh | Wisconsin | 18500 | Oshkosh |
| 446 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Findlay | Ohio | 18300 | Marathon Petroleum |
| 447 | 90802 | 34 | -118 | 39,859 | POINT (-118.21143 33.75035) | Long Beach | California | 18000 | Molina Healthcare |
| 448 | 33322 | 26 | -80 | 40,522 | POINT (-80.27429 26.14997) | Plantation | Florida | 18000 | Chewy |
| 449 | 48152 | 42 | -83 | 30,394 | POINT (-83.37433 42.42597) | Livonia | Michigan | 18000 | Masco |
| 450 | 94404 | 38 | -122 | 35,950 | POINT (-122.26905 37.5562) | Foster City | California | 17600 | Gilead Sciences |
| 451 | 85281 | 33 | -112 | 70,726 | POINT (-111.93157 33.42805) | Tempe | Arizona | 17400 | Carvana |
| 452 | 46580 | 41 | -86 | 21,812 | POINT (-85.87212 41.20884) | Warsaw | Indiana | 17000 | Zimmer Biomet s |
| 453 | 33408 | 27 | -80 | 18,766 | POINT (-80.05677 26.84115) | Juno Beach | Florida | 16800 | NextEra Energy |
| 454 | 80021 | 40 | -105 | 35,562 | POINT (-105.11448 39.89105) | Westminster | Colorado | 16000 | Ball |
| 455 | 94086 | 37 | -122 | 48,956 | POINT (-122.02316 37.37164) | Sunnyvale | California | 15600 | Intuitive Surgical |
| 456 | 95035 | 37 | -122 | 78,479 | POINT (-121.87632 37.44319) | Milpitas | California | 15100 | KLA |
| 457 | 90266 | 34 | -118 | 34,584 | POINT (-118.39705 33.88968) | Manhattan Beach | California | 15100 | Skechers U.S.A. |
| 458 | 10591 | 41 | -74 | 23,663 | POINT (-73.84653 41.08436) | Tarrytown | New York | 15100 | Regeneron Pharmaceuticals |
| 459 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | Vernon Hills | Illinois | 15100 | CDW |
| 460 | 33160 | 26 | -80 | 43,225 | POINT (-80.13583 25.93234) | Sunny Isles Beach | Florida | 15000 | Icahn Enterprises |
| 461 | 49315 | 43 | -86 | 26,123 | POINT (-85.73589 42.80101) | Byron Center | Michigan | 15000 | SpartanNash |
| 462 | 76011 | 33 | -97 | 22,297 | POINT (-97.08223 32.7543) | Arlington | Texas | 14800 | D.R. Horton |
| 463 | 08103 | 40 | -75 | 13,137 | POINT (-75.11275 39.93533) | Camden | New Jersey | 14400 | Campbell's |
| 464 | 21231 | 39 | -77 | 14,556 | POINT (-76.592 39.28775) | Baltimore | Maryland | 14200 | Constellation Energy |
| 465 | 37660 | 37 | -83 | 40,114 | POINT (-82.57339 36.52938) | Kingsport | Tennessee | 14000 | Eastman Chemical |
| 466 | 66202 | 39 | -95 | 17,321 | POINT (-94.66909 39.02392) | Merriam | Kansas | 14000 | Seaboard |
| 467 | 91770 | 34 | -118 | 58,893 | POINT (-118.08361 34.06395) | Rosemead | California | 14000 | Edison International |
| 468 | 95032 | 37 | -122 | 27,682 | POINT (-121.92359 37.20859) | Los Gatos | California | 14000 | Netflix |
| 469 | 46804 | 41 | -85 | 29,177 | POINT (-85.23913 41.05421) | Fort Wayne | Indiana | 13000 | Steel Dynamics |
| 470 | 31999 | 32 | -85 | 3,469 | POINT (-84.98772 32.46078) | Columbus | Georgia | 12700 | Aflac |
| 471 | 60523 | 42 | -88 | 10,012 | POINT (-87.95406 41.83713) | Oak Brook | Illinois | 12500 | Ace Hardware |
| 472 | 70113 | 30 | -90 | 9,888 | POINT (-90.08382 29.9422) | New Orleans | Louisiana | 12300 | Entergy |
| 473 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | El Dorado | Arkansas | 11600 | Murphy USA |
| 474 | 60154 | 42 | -88 | 16,524 | POINT (-87.88986 41.84923) | Westchester | Illinois | 11200 | Ingredion |
| 475 | 53783 | 43 | -89 | 0 | POINT (-89.4012 43.0731) | Madison | Wisconsin | 11100 | American Family Insurance |
| 476 | 74172 | 36 | -96 | 0 | POINT (-95.9905 36.1544) | Tulsa | Oklahoma | 11000 | Williams |
| 477 | 74103 | 36 | -96 | 2,419 | POINT (-95.9957 36.15617) | Tulsa | Oklahoma | 11000 | Oneok |
| 478 | 37402 | 35 | -85 | 4,203 | POINT (-85.31553 35.04672) | Chattanooga | Tennessee | 10900 | Unum |
| 479 | 55077 | 45 | -93 | 14,585 | POINT (-93.07574 44.81989) | Inver Grove Heights | Minnesota | 10700 | CHS |
| 480 | 94403 | 38 | -122 | 43,459 | POINT (-122.30454 37.53844) | San Mateo | California | 10200 | Franklin Resources |
| 481 | 91367 | 34 | -119 | 45,427 | POINT (-118.61518 34.17708) | Woodland Hills | California | 9900 | Farmers Insurance Exchange |
| 482 | 19087 | 40 | -75 | 33,770 | POINT (-75.40004 40.06172) | Radnor | Pennsylvania | 9800 | Lincoln National |
| 483 | 14564 | 43 | -77 | 16,257 | POINT (-77.42417 42.98329) | Victor | New York | 9300 | Constellation Brands |
| 484 | 55126 | 45 | -93 | 27,484 | POINT (-93.13581 45.08614) | Arden Hills | Minnesota | 9000 | Land O'Lakes |
| 485 | 44667 | 41 | -82 | 13,688 | POINT (-81.76495 40.83386) | Orrville | Ohio | 9000 | J.M. Smucker |
| 486 | 49201 | 42 | -84 | 49,114 | POINT (-84.38301 42.25213) | Jackson | Michigan | 8300 | CMS Energy |
| 487 | 20170 | 39 | -77 | 43,372 | POINT (-77.38042 38.98075) | Herndon | Virginia | 8100 | QXO Building Products |
| 488 | 78130 | 30 | -98 | 95,787 | POINT (-98.06877 29.69224) | New Braunfels | Texas | 7900 | Rush Enterprises |
| 489 | 48917 | 43 | -85 | 32,029 | POINT (-84.63897 42.72509) | Lansing | Michigan | 7300 | Auto-Owners Insurance |
| 490 | 16530 | 42 | -80 | 94,831 | POINT (-80.08204 42.13039) | Erie | Pennsylvania | 6700 | Erie Insurance |
| 491 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | Corona | California | 6000 | Monster Beverage |
| 492 | 02919 | 42 | -72 | 29,473 | POINT (-71.52002 41.82733) | Johnston | Rhode Island | 5800 | FM |
| 493 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | Fairfield | Ohio | 5600 | Cincinnati Financial |
| 494 | 19034 | 40 | -75 | 7,084 | POINT (-75.20953 40.13353) | Fort Washington | Pennsylvania | 4900 | Toll Brothers |
| 495 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | Chesterfield | Missouri | 4100 | Reinsurance of America |
| 496 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Oklahoma City | Oklahoma | 2300 | Devon Energy |
| 497 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Midland | Texas | 2000 | Diamondback Energy |
| 498 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | El Segundo | California | 500 | A-Mark Precious Metals |
In [187]:
mctte = gdfusactctte.explore(column='Employees', name='Total Employees in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctte)
mctte
Out[187]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [188]:
# Check Average Number of Employee in each City
dfctavremp = df.groupby(['City','State'])[df.columns[[6]]].mean('Employees').sort_values('Employees', ascending=False)
dfctavremp
Out[188]:
| Employees | ||
|---|---|---|
| City | State | |
| Bentonville | Arkansas | 2,100,000 |
| Newark | California | 450,000 |
| Framingham | Massachusetts | 364,000 |
| Seattle | Washington | 350,267 |
| Teaneck | New Jersey | 336,800 |
| Issaquah | Washington | 333,000 |
| Armonk | New York | 284,500 |
| Nashville | Tennessee | 271,000 |
| Woonsocket | Rhode Island | 259,500 |
| Lakeland | Florida | 255,000 |
| Plano | Texas | 245,500 |
| Redmond | Washington | 228,000 |
| Philadelphia | Pennsylvania | 224,350 |
| Mooresville | North Carolina | 215,500 |
| Eden Prairie | Minnesota | 206,900 |
| Burbank | California | 205,000 |
| Goodlettsville | Tennessee | 194,200 |
| Orlando | Florida | 191,100 |
| Memphis | Tennessee | 186,633 |
| Purchase | New York | 177,150 |
| Southfield | Michigan | 173,700 |
| Dearborn | Michigan | 171,000 |
| Cupertino | California | 164,000 |
| Deerfield | Illinois | 145,250 |
| Austin | Texas | 142,350 |
| Chesapeake | Virginia | 139,600 |
| New Brunswick | New Jersey | 138,100 |
| Bethesda | Maryland | 138,000 |
| Springdale | Arkansas | 138,000 |
| Fort Worth | Texas | 133,300 |
| Ashburn | Virginia | 130,000 |
| Wallingford | Connecticut | 125,000 |
| Arlington | Virginia | 122,367 |
| Boise | Idaho | 122,300 |
| Omaha | Nebraska | 115,775 |
| Abbott Park | Illinois | 114,000 |
| Round Rock | Texas | 108,000 |
| Dublin | California | 107,000 |
| Mountain View | California | 103,750 |
| Cincinnati | Ohio | 98,917 |
| Falls Church | Virginia | 97,000 |
| Minneapolis | Minnesota | 95,550 |
| Atlanta | Georgia | 94,900 |
| Durham | North Carolina | 88,000 |
| King of Prussia | Pennsylvania | 87,500 |
| Springfield | Missouri | 85,600 |
| Richfield | Minnesota | 85,000 |
| Beaverton | Oregon | 79,400 |
| St. Petersburg | Florida | 78,500 |
| Menlo Park | California | 74,100 |
| Rahway | New Jersey | 74,000 |
| Franklin Lakes | New Jersey | 74,000 |
| Bloomfield | Connecticut | 72,400 |
| Farmington | Connecticut | 72,000 |
| Charlotte | North Carolina | 70,450 |
| Columbus | Indiana | 69,600 |
| McLean | Virginia | 68,975 |
| Newport Beach | California | 67,400 |
| Bloomington | Illinois | 67,400 |
| Mayfield Village | Ohio | 66,300 |
| Dallas | Texas | 65,567 |
| Burlington | North Carolina | 65,400 |
| Waltham | Massachusetts | 64,400 |
| Roseland | New Jersey | 64,000 |
| Spring | Texas | 60,950 |
| Detroit | Michigan | 60,733 |
| Menomonee Falls | Wisconsin | 60,000 |
| Indianapolis | Indiana | 57,567 |
| Stamford | Connecticut | 56,375 |
| Corning | New York | 56,300 |
| Rolling Meadows | Illinois | 56,000 |
| Moline | Illinois | 55,500 |
| Northbrook | Illinois | 55,200 |
| North Chicago | Illinois | 55,000 |
| Des Peres | Missouri | 55,000 |
| San Francisco | California | 54,667 |
| Las Vegas | Nevada | 54,550 |
| Portage | Michigan | 53,000 |
| Evendale | Ohio | 53,000 |
| Franklin | Tennessee | 52,500 |
| Chicago | Illinois | 51,757 |
| Secaucus | New Jersey | 50,500 |
| Auburn Hills | Michigan | 50,300 |
| Reno | Nevada | 50,000 |
| New Britain | Connecticut | 48,500 |
| Dublin | Ohio | 48,400 |
| Palm Beach Gardens | Florida | 48,000 |
| Palo Alto | California | 47,500 |
| Burlington | New Jersey | 47,300 |
| New York | New York | 47,167 |
| Melbourne | Florida | 47,000 |
| Antioch | Tennessee | 47,000 |
| Greenwich | Connecticut | 44,900 |
| Louisville | Kentucky | 44,800 |
| Benton Harbor | Michigan | 44,000 |
| Glenview | Illinois | 44,000 |
| Reston | Virginia | 44,000 |
| Conshohocken | Pennsylvania | 44,000 |
| Marlborough | Massachusetts | 43,000 |
| Cambridge | Massachusetts | 42,200 |
| Evansville | Indiana | 42,000 |
| Calhoun | Georgia | 41,900 |
| Santa Clara | California | 41,700 |
| Coral Gables | Florida | 41,350 |
| Akron | Ohio | 40,150 |
| Newport News | Virginia | 39,500 |
| Bolingbrook | Illinois | 39,000 |
| Sumner | Washington | 39,000 |
| St. Paul | Minnesota | 38,367 |
| Cleveland | Ohio | 37,680 |
| Coraopolis | Pennsylvania | 37,400 |
| Midland | Michigan | 36,000 |
| Irving | Texas | 35,875 |
| San Jose | California | 35,457 |
| Mentor | Ohio | 35,000 |
| Princeton | New Jersey | 34,100 |
| Lowell | Arkansas | 33,600 |
| Ankeny | Iowa | 33,100 |
| Raleigh | North Carolina | 32,650 |
| Norwalk | Connecticut | 32,300 |
| St. Louis | Missouri | 32,140 |
| Westlake | Texas | 32,100 |
| Canonsburg | Pennsylvania | 32,000 |
| Washington | District of Columbia | 31,067 |
| Westerville | Ohio | 31,000 |
| Denver | Colorado | 30,950 |
| Phoenix | Arizona | 30,250 |
| Medford | Oregon | 30,200 |
| Rosemont | Illinois | 30,000 |
| Pittsburgh | Pennsylvania | 29,971 |
| Burlington | Massachusetts | 29,400 |
| Bloomfield Hills | Michigan | 28,900 |
| Jacksonville | Florida | 28,725 |
| Thousand Oaks | California | 28,000 |
| Providence | Rhode Island | 26,533 |
| Irvine | California | 26,100 |
| Estero | Florida | 26,000 |
| Newark | New Jersey | 25,450 |
| Fort Lauderdale | Florida | 25,100 |
| Melville | New York | 25,000 |
| Monroe | Louisiana | 25,000 |
| San Diego | California | 24,933 |
| Bellevue | Washington | 24,500 |
| Downers Grove | Illinois | 24,000 |
| Wilmington | Massachusetts | 24,000 |
| Delaware | 24,000 | |
| San Antonio | Texas | 23,950 |
| Houston | Texas | 23,233 |
| Boston | Massachusetts | 23,100 |
| Glen Allen | Virginia | 22,600 |
| Elkhart | Indiana | 22,300 |
| Buffalo | New York | 22,100 |
| Maplewood | Minnesota | 22,000 |
| Summit | New Jersey | 22,000 |
| Fremont | California | 21,600 |
| Centennial | Colorado | 21,500 |
| Milwaukee | Wisconsin | 21,380 |
| Winona | Minnesota | 21,000 |
| Riverwoods | Illinois | 21,000 |
| Maumee | Ohio | 20,950 |
| Brentwood | Tennessee | 20,500 |
| Pleasanton | California | 20,500 |
| Lake Forest | Illinois | 20,200 |
| Austin | Minnesota | 20,000 |
| Oakland | California | 19,900 |
| Richmond | Virginia | 19,860 |
| Des Moines | Iowa | 19,700 |
| Columbus | Ohio | 19,567 |
| Duluth | Georgia | 19,500 |
| Hershey | Pennsylvania | 19,300 |
| Hartford | Connecticut | 19,100 |
| Oshkosh | Wisconsin | 18,500 |
| Tampa | Florida | 18,400 |
| Chandler | Arizona | 18,300 |
| Findlay | Ohio | 18,300 |
| Livonia | Michigan | 18,000 |
| Plantation | Florida | 18,000 |
| Long Beach | California | 18,000 |
| Foster City | California | 17,600 |
| Tempe | Arizona | 17,400 |
| Beverly Hills | California | 17,100 |
| Warsaw | Indiana | 17,000 |
| Juno Beach | Florida | 16,800 |
| Englewood | Colorado | 16,350 |
| Westminster | Colorado | 16,000 |
| Birmingham | Alabama | 15,800 |
| Sunnyvale | California | 15,600 |
| Long Island City | New York | 15,350 |
| Tarrytown | New York | 15,100 |
| Vernon Hills | Illinois | 15,100 |
| Milpitas | California | 15,100 |
| Manhattan Beach | California | 15,100 |
| Byron Center | Michigan | 15,000 |
| Sunny Isles Beach | Florida | 15,000 |
| Arlington | Texas | 14,800 |
| Allentown | Pennsylvania | 14,550 |
| Camden | New Jersey | 14,400 |
| Baltimore | Maryland | 14,200 |
| Rosemead | California | 14,000 |
| Kingsport | Tennessee | 14,000 |
| Los Gatos | California | 14,000 |
| Merriam | Kansas | 14,000 |
| Redwood City | California | 13,650 |
| Fort Wayne | Indiana | 13,000 |
| Toledo | Ohio | 12,850 |
| Parsippany | New Jersey | 12,733 |
| Columbus | Georgia | 12,700 |
| Oak Brook | Illinois | 12,500 |
| New Orleans | Louisiana | 12,300 |
| El Dorado | Arkansas | 11,600 |
| Westchester | Illinois | 11,200 |
| Madison | Wisconsin | 11,100 |
| Springfield | Massachusetts | 10,950 |
| Chattanooga | Tennessee | 10,900 |
| Inver Grove Heights | Minnesota | 10,700 |
| San Mateo | California | 10,200 |
| Woodland Hills | California | 9,900 |
| Radnor | Pennsylvania | 9,800 |
| Scottsdale | Arizona | 9,500 |
| Victor | New York | 9,300 |
| Arden Hills | Minnesota | 9,000 |
| Orrville | Ohio | 9,000 |
| Miami | Florida | 8,433 |
| Jackson | Michigan | 8,300 |
| Herndon | Virginia | 8,100 |
| New Braunfels | Texas | 7,900 |
| Lansing | Michigan | 7,300 |
| Erie | Pennsylvania | 6,700 |
| Corona | California | 6,000 |
| Johnston | Rhode Island | 5,800 |
| Fairfield | Ohio | 5,600 |
| Tulsa | Oklahoma | 5,500 |
| Fort Washington | Pennsylvania | 4,900 |
| Chesterfield | Missouri | 4,100 |
| Oklahoma City | Oklahoma | 2,300 |
| Midland | Texas | 2,000 |
| El Segundo | California | 500 |
In [189]:
# Join the Dataframe 'gdfusact' with 'dfctavremp' for the Top 10
dfctavremp = dfctavremp.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctavremp = gdfusact.merge(dfctavremp, how = 'inner', on = ['Zip Code'])
gdfusactctavremp = gdfusactctavremp.sort_values('Employees', ascending=False).reset_index(drop=True)
In [190]:
mctavremp = gdfusactctavremp.explore(column='Employees', name='Average Number of Employees in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctavremp)
mctavremp
Out[190]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [191]:
# Check the Most Efficient Company in each City
dfctmaxeffco = df.head(1)
dfctmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
dfctmaxeffco = pd.concat([dfctmaxeffco, dfct.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
dfctmaxeffco = dfctmaxeffco.drop(0)
dfctmaxeffco[['City','State','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[191]:
| City | State | Company | Industry | Zip Code | Efficiency | |
|---|---|---|---|---|---|---|
| 0 | New York | New York | StoneX | Diversified Financials | 10169 | 22,200,000 |
| 1 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 19,400,000 |
| 2 | Washington | District of Columbia | Fannie Mae | Diversified Financials | 20005 | 18,621,951 |
| 3 | McLean | Virginia | Freddie Mac | Diversified Financials | 22102 | 15,074,074 |
| 4 | San Antonio | Texas | Valero Energy | Petroleum Refining | 78249 | 12,525,253 |
| 5 | Houston | Texas | Plains GP | Pipelines | 77002 | 11,928,571 |
| 6 | Toledo | Ohio | Welltower | Real Estate | 43615 | 11,428,571 |
| 7 | Miami | Florida | World Kinect | Energy | 33178 | 8,978,723 |
| 8 | Parsippany | New Jersey | PBF Energy | Petroleum Refining | 07054 | 8,487,179 |
| 9 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 7,672,131 |
| 10 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 6,913,043 |
| 11 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 6,681,818 |
| 12 | Irving | Texas | McKesson | Wholesalers: Health Care | 75039 | 6,437,500 |
| 13 | Brentwood | Tennessee | Delek US | Petroleum Refining | 37027 | 6,250,000 |
| 14 | Denver | Colorado | Ovintiv | Mining, Crude-Oil Production | 80202 | 5,750,000 |
| 15 | Spring | Texas | Exxon Mobil | Petroleum Refining | 77389 | 5,740,558 |
| 16 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 5,550,000 |
| 17 | Dallas | Texas | HF Sinclair | Petroleum Refining | 75219 | 5,396,226 |
| 18 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 5,390,244 |
| 19 | Cincinnati | Ohio | Western & Southern Financial | Insurance: Life, Health (Mutual) | 45202 | 5,111,111 |
| 20 | Milwaukee | Wisconsin | Northwestern Mutual | Insurance: Life, Health (Mutual) | 53202 | 5,048,780 |
| 21 | Maumee | Ohio | Andersons | Food Production | 43537 | 4,913,043 |
| 22 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 4,685,950 |
| 23 | Waltham | Massachusetts | Global Partners | Energy | 02453 | 4,526,316 |
| 24 | Tulsa | Oklahoma | Oneok | Pipelines | 74103 | 4,173,077 |
| 25 | Springfield | Massachusetts | Mass Mutual | Insurance: Life, Health (Mutual) | 01111 | 3,848,214 |
| 26 | Newport Beach | California | Pacific Life | Insurance: Life, Health (Stock) | 92660 | 3,674,419 |
| 27 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 3,672,897 |
| 28 | Santa Clara | California | Nvidia | Semiconductors and Other Electronic Components | 95051 | 3,625,000 |
| 29 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 3,412,983 |
| 30 | Richmond | Virginia | Altria | Tobacco | 23230 | 3,290,323 |
| 31 | Greenwich | Connecticut | Interactive Brokers | Securities | 06830 | 3,133,333 |
| 32 | San Francisco | California | Prologis | Real Estate | 94111 | 3,037,037 |
| 33 | Los Gatos | California | Netflix | Entertainment | 95032 | 2,785,714 |
| 34 | Scottsdale | Arizona | Taylor Morrison Home | Homebuilders | 85251 | 2,733,333 |
| 35 | Minneapolis | Minnesota | Thrivent Financial for Lutherans | Insurance: Life, Health (Mutual) | 55415 | 2,725,000 |
| 36 | St. Louis | Missouri | Centene | Health Care: Insurance and Managed Care | 63105 | 2,695,868 |
| 37 | Atlanta | Georgia | Pulte | Homebuilders | 30326 | 2,632,353 |
| 38 | San Jose | California | Super Micro Computer | Computers, Office Equipment | 95131 | 2,631,579 |
| 39 | Columbus | Ohio | Nationwide | Insurance: Property and Casualty (Mutual) | 43215 | 2,604,444 |
| 40 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 2,486,486 |
| 41 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 2,384,146 |
| 42 | Boston | Massachusetts | American Tower | Real Estate | 02116 | 2,340,426 |
| 43 | Fremont | California | TD Synnex | Wholesalers: Electronics and Office Equipment | 94538 | 2,267,442 |
| 44 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 2,255,556 |
| 45 | Omaha | Nebraska | Mutual of Omaha Insurance | Insurance: Life, Health (Mutual) | 68175 | 2,246,154 |
| 46 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 2,219,973 |
| 47 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 2,204,082 |
| 48 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 2,164,384 |
| 49 | Oakland | California | Block | Financial Data Services | 94612 | 2,114,035 |
| 50 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 2,017,857 |
| 51 | Chicago | Illinois | Archer Daniels Midland | Food Production | 60601 | 1,979,167 |
| 52 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 1,970,149 |
| 53 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 1,918,919 |
| 54 | Mountain View | California | Alphabet | Internet Services and Retailing | 94043 | 1,909,438 |
| 55 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 1,877,551 |
| 56 | Newark | New Jersey | Prudential Financial | Insurance: Life, Health (Stock) | 07102 | 1,857,520 |
| 57 | Jacksonville | Florida | GuideWell Mutual | Insurance: Life, Health (Stock) | 32246 | 1,843,575 |
| 58 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 1,839,080 |
| 59 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 1,824,926 |
| 60 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 1,800,000 |
| 61 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 1,793,103 |
| 62 | Louisville | Kentucky | Humana | Health Care: Insurance and Managed Care | 40202 | 1,792,998 |
| 63 | Indianapolis | Indiana | Elevance Health | Health Care: Insurance and Managed Care | 46204 | 1,706,847 |
| 64 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 1,661,972 |
| 65 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 1,636,364 |
| 66 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 1,565,657 |
| 67 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 1,543,103 |
| 68 | Phoenix | Arizona | Avnet | Wholesalers: Electronics and Office Equipment | 85034 | 1,535,484 |
| 69 | Detroit | Michigan | Ally Financial | Diversified Financials | 48226 | 1,532,710 |
| 70 | Reston | Virginia | NVR | Homebuilders | 20190 | 1,528,571 |
| 71 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 1,488,189 |
| 72 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 1,476,190 |
| 73 | St. Paul | Minnesota | Securian Financial | Insurance: Life, Health (Stock) | 55101 | 1,464,286 |
| 74 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 1,436,609 |
| 75 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 1,416,422 |
| 76 | Palo Alto | California | Broadcom | Semiconductors and Other Electronic Components | 94304 | 1,416,216 |
| 77 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 1,390,728 |
| 78 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 1,387,435 |
| 79 | San Diego | California | LPL Financial s | Securities | 92121 | 1,377,778 |
| 80 | Arlington | Virginia | AES | Utilities: Gas and Electric | 22203 | 1,351,648 |
| 81 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 1,346,154 |
| 82 | Charlotte | North Carolina | Sonic Automotive | Automotive Retailing, Services | 28211 | 1,314,815 |
| 83 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 1,297,674 |
| 84 | Eden Prairie | Minnesota | C.H. Robinson Worldwide | Transportation and Logistics | 55347 | 1,282,609 |
| 85 | Cambridge | Massachusetts | Biogen | Pharmaceuticals | 02142 | 1,276,316 |
| 86 | Allentown | Pennsylvania | PPL | Utilities: Gas and Electric | 18101 | 1,268,657 |
| 87 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 1,263,333 |
| 88 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 1,257,143 |
| 89 | Corona | California | Monster Beverage | Beverages | 92879 | 1,250,000 |
| 90 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 1,211,921 |
| 91 | Stamford | Connecticut | Synchrony Financial | Diversified Financials | 06902 | 1,210,000 |
| 92 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 1,209,877 |
| 93 | Midland | Michigan | Dow | Chemicals | 48674 | 1,194,444 |
| 94 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 1,192,857 |
| 95 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 1,183,486 |
| 96 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 1,161,232 |
| 97 | Englewood | Colorado | EchoStar | Telecommunications | 80112 | 1,153,285 |
| 98 | Duluth | Georgia | Asbury Automotive | Automotive Retailing, Services | 30097 | 1,146,667 |
| 99 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 1,137,255 |
| 100 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 1,123,810 |
| 101 | Bellevue | Washington | Paccar | Motor Vehicles & Parts | 98004 | 1,119,601 |
| 102 | Providence | Rhode Island | United Natural Foods | Wholesalers: Food and Grocery | 02908 | 1,095,406 |
| 103 | Pittsburgh | Pennsylvania | WESCO International | Wholesalers: Diversified | 15219 | 1,090,000 |
| 104 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 1,081,871 |
| 105 | Victor | New York | Constellation Brands | Beverages | 14564 | 1,075,269 |
| 106 | Redmond | Washington | Microsoft | Computer Software | 98052 | 1,075,000 |
| 107 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 1,067,729 |
| 108 | Akron | Ohio | FirstEnergy | Utilities: Gas and Electric | 44308 | 1,056,911 |
| 109 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 1,055,363 |
| 110 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 1,023,636 |
| 111 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 987,342 |
| 112 | Norwalk | Connecticut | Booking s | Internet Services and Retailing | 06854 | 979,339 |
| 113 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 967,480 |
| 114 | Beverly Hills | California | Live Nation Entertainment | Entertainment | 90210 | 958,678 |
| 115 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 940,397 |
| 116 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 931,532 |
| 117 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 911,111 |
| 118 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 903,614 |
| 119 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 885,185 |
| 120 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 867,568 |
| 121 | Raleigh | North Carolina | First Citizens BancShares | Commercial Banks | 27609 | 867,052 |
| 122 | Newport News | Virginia | Ferguson | Wholesalers: Diversified | 23606 | 845,714 |
| 123 | San Mateo | California | Franklin Resources | Securities | 94403 | 833,333 |
| 124 | Seattle | Washington | Expedia | Internet Services and Retailing | 98119 | 830,303 |
| 125 | Long Island City | New York | Altice USA | Telecommunications | 11101 | 825,688 |
| 126 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 817,259 |
| 127 | Westlake | Texas | Charles Schwab | Securities | 76262 | 809,969 |
| 128 | Tampa | Florida | Mosaic | Chemicals | 33602 | 804,348 |
| 129 | Purchase | New York | Mastercard | Financial Data Services | 10577 | 798,867 |
| 130 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 787,356 |
| 131 | St. Petersburg | Florida | Raymond James Financial | Securities | 33716 | 784,211 |
| 132 | Austin | Texas | Tesla | Motor Vehicles & Parts | 78725 | 777,247 |
| 133 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 764,264 |
| 134 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 760,000 |
| 135 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 756,250 |
| 136 | Glen Allen | Virginia | Markel | Insurance: Property and Casualty (Stock) | 23060 | 754,545 |
| 137 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 730,189 |
| 138 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 704,545 |
| 139 | Lake Forest | Illinois | W.W. Grainger | Wholesalers: Diversified | 60045 | 688,000 |
| 140 | Philadelphia | Pennsylvania | Comcast | Telecommunications | 19103 | 679,670 |
| 141 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 671,429 |
| 142 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 666,667 |
| 143 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 666,667 |
| 144 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 661,111 |
| 145 | Westchester | Illinois | Ingredion | Food Production | 60154 | 660,714 |
| 146 | Merriam | Kansas | Seaboard | Food Production | 66202 | 650,000 |
| 147 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 649,007 |
| 148 | Beaverton | Oregon | Nike | Apparel | 97005 | 647,355 |
| 149 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 643,012 |
| 150 | Cleveland | Ohio | Cleveland-Cliffs | Metals | 44114 | 640,000 |
| 151 | Redwood City | California | Equinix | Real Estate | 94065 | 639,706 |
| 152 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 633,333 |
| 153 | Marlborough | Massachusetts | BJ's Wholesale Club | General Merchandisers | 01752 | 621,212 |
| 154 | Birmingham | Alabama | Vulcan Materials | Building Materials, Glass | 35242 | 616,667 |
| 155 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 610,860 |
| 156 | Chandler | Arizona | Insight Enterprises | Information Technology Services | 85286 | 608,392 |
| 157 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 596,026 |
| 158 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 595,000 |
| 159 | Bethesda | Maryland | Lockheed Martin | Aerospace & Defense | 20817 | 586,777 |
| 160 | Deerfield | Illinois | Walgreens | Food & Drug Stores | 60015 | 584,950 |
| 161 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 580,311 |
| 162 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 578,378 |
| 163 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 538,462 |
| 164 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 524,000 |
| 165 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 523,810 |
| 166 | Boise | Idaho | Micron Technology | Semiconductors and Other Electronic Components | 83716 | 522,917 |
| 167 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 516,667 |
| 168 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 516,667 |
| 169 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 508,000 |
| 170 | Memphis | Tennessee | International Paper | Packaging, Containers | 38197 | 502,703 |
| 171 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 489,943 |
| 172 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 488,235 |
| 173 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 459,375 |
| 174 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 453,191 |
| 175 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 452,941 |
| 176 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 450,151 |
| 177 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 448,430 |
| 178 | Burbank | California | Walt Disney | Entertainment | 91521 | 445,854 |
| 179 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 433,333 |
| 180 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 426,415 |
| 181 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 422,680 |
| 182 | Pleasanton | California | Workday | Computer Software | 94588 | 409,756 |
| 183 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 406,602 |
| 184 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 391,667 |
| 185 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 388,399 |
| 186 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 386,232 |
| 187 | Coral Gables | Florida | MasTec | Engineering & Construction | 33134 | 384,375 |
| 188 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 377,273 |
| 189 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 377,273 |
| 190 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 368,421 |
| 191 | Auburn Hills | Michigan | BorgWarner | Motor Vehicles & Parts | 48326 | 368,146 |
| 192 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 361,364 |
| 193 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 360,119 |
| 194 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 358,289 |
| 195 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 357,143 |
| 196 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 350,000 |
| 197 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 346,154 |
| 198 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 324,286 |
| 199 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 317,526 |
| 200 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 306,383 |
| 201 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 300,000 |
| 202 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 296,364 |
| 203 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 292,857 |
| 204 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 289,744 |
| 205 | Las Vegas | Nevada | Las Vegas Sands | Hotels, Casinos, Resorts | 89113 | 281,796 |
| 206 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 272,973 |
| 207 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 271,795 |
| 208 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 270,000 |
| 209 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 260,517 |
| 210 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 258,065 |
| 211 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 257,757 |
| 212 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 251,429 |
| 213 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 240,000 |
| 214 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 236,078 |
| 215 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 232,682 |
| 216 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 226,000 |
| 217 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 224,101 |
| 218 | Armonk | New York | IBM | Information Technology Services | 10504 | 220,738 |
| 219 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 220,630 |
| 220 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 209,063 |
| 221 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 207,143 |
| 222 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 198,777 |
| 223 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 198,611 |
| 224 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 197,196 |
| 225 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 196,040 |
| 226 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 195,093 |
| 227 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 180,571 |
| 228 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 175,000 |
| 229 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 154,945 |
| 230 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 134,139 |
| 231 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 121,600 |
| 232 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 105,385 |
| 233 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 59,655 |
| 234 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 58,492 |
| 235 | Plano | Texas | Yum China s | Food Services | 75074 | 46,029 |
| 236 | Newark | California | Concentrix | Information Technology Services | 94560 | 21,333 |
In [192]:
# Join the Dataframe 'gdfusact' with 'dfctmaxeffco' for the Top 10
gdfusactmaxeffco = gdfusact.merge(dfctmaxeffco, how = 'inner', on = ['Zip Code'])
gdfusactmaxeffco = gdfusactmaxeffco.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [193]:
mctmaxeffco = gdfusactmaxeffco.explore(column='Efficiency', name='The Most Efficient Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxeffco)
mctmaxeffco
Out[193]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [194]:
# Check the Least Efficient Company in each City
dfctmineffco = df.head(1)
dfctmineffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
dfctmineffco = pd.concat([dfctmineffco, dfct.sort_values(by='Efficiency',ascending=True).head(1)], ignore_index=True)
dfctmineffco = dfctmineffco.drop(0)
dfctmineffco[['City','State','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[194]:
| City | State | Company | Industry | Zip Code | Efficiency | |
|---|---|---|---|---|---|---|
| 0 | El Segundo | California | A-Mark Precious Metals | Wholesalers: Diversified | 90245 | 19,400,000 |
| 1 | Findlay | Ohio | Marathon Petroleum | Petroleum Refining | 45840 | 7,672,131 |
| 2 | Oklahoma City | Oklahoma | Devon Energy | Mining, Crude-Oil Production | 73102 | 6,913,043 |
| 3 | Conshohocken | Pennsylvania | Cencora | Wholesalers: Health Care | 19428 | 6,681,818 |
| 4 | Midland | Texas | Diamondback Energy | Mining, Crude-Oil Production | 79701 | 5,550,000 |
| 5 | Chesterfield | Missouri | Reinsurance of America | Insurance: Life, Health (Stock) | 63017 | 5,390,244 |
| 6 | Dublin | Ohio | Cardinal Health | Wholesalers: Health Care | 43017 | 4,685,950 |
| 7 | Inver Grove Heights | Minnesota | CHS | Food Production | 55077 | 3,672,897 |
| 8 | Bloomfield | Connecticut | Cigna | Health Care: Pharmacy and Other Services | 06002 | 3,412,983 |
| 9 | Los Gatos | California | Netflix | Entertainment | 95032 | 2,785,714 |
| 10 | Arlington | Texas | D.R. Horton | Homebuilders | 76011 | 2,486,486 |
| 11 | Cupertino | California | Apple | Computers, Office Equipment | 95014 | 2,384,146 |
| 12 | Long Beach | California | Molina Healthcare | Health Care: Insurance and Managed Care | 90802 | 2,255,556 |
| 13 | Menlo Park | California | Meta | Internet Services and Retailing | 94025 | 2,219,973 |
| 14 | Fort Washington | Pennsylvania | Toll Brothers | Homebuilders | 19034 | 2,204,082 |
| 15 | Lansing | Michigan | Auto-Owners Insurance | Insurance: Property and Casualty (Mutual) | 48917 | 2,164,384 |
| 16 | Fairfield | Ohio | Cincinnati Financial | Insurance: Property and Casualty (Stock) | 45014 | 2,017,857 |
| 17 | Erie | Pennsylvania | Erie Insurance | Insurance: Property and Casualty (Mutual) | 16530 | 1,970,149 |
| 18 | Madison | Wisconsin | American Family Insurance | Insurance: Property and Casualty (Stock) | 53783 | 1,918,919 |
| 19 | Radnor | Pennsylvania | Lincoln National | Insurance: Life, Health (Stock) | 19087 | 1,877,551 |
| 20 | Irvine | California | Ingram Micro | Wholesalers: Electronics and Office Equipment | 92612 | 1,839,080 |
| 21 | Bloomington | Illinois | State Farm | Insurance: Property and Casualty (Mutual) | 61710 | 1,824,926 |
| 22 | Tulsa | Oklahoma | Williams | Pipelines | 74172 | 1,810,345 |
| 23 | Arden Hills | Minnesota | Land O'Lakes | Food Consumer Products | 55126 | 1,800,000 |
| 24 | Johnston | Rhode Island | FM | Insurance: Property and Casualty (Stock) | 02919 | 1,793,103 |
| 25 | Baltimore | Maryland | Constellation Energy | Energy | 21231 | 1,661,972 |
| 26 | Foster City | California | Gilead Sciences | Pharmaceuticals | 94404 | 1,636,364 |
| 27 | Woodland Hills | California | Farmers Insurance Exchange | Insurance: Property and Casualty (Mutual) | 91367 | 1,565,657 |
| 28 | El Dorado | Arkansas | Murphy USA | Specialty Retailers: Other | 71730 | 1,543,103 |
| 29 | Columbus | Georgia | Aflac | Insurance: Life, Health (Stock) | 31999 | 1,488,189 |
| 30 | Juno Beach | Florida | NextEra Energy | Utilities: Gas and Electric | 33408 | 1,476,190 |
| 31 | Woonsocket | Rhode Island | CVS Health | Health Care: Pharmacy and Other Services | 02895 | 1,436,609 |
| 32 | Princeton | New Jersey | Bristol-Myers Squibb | Pharmaceuticals | 08543 | 1,416,422 |
| 33 | Vernon Hills | Illinois | CDW | Information Technology Services | 60061 | 1,390,728 |
| 34 | Hartford | Connecticut | Hartford Insurance | Insurance: Property and Casualty (Stock) | 06155 | 1,387,435 |
| 35 | Fort Wayne | Indiana | Steel Dynamics | Metals | 46804 | 1,346,154 |
| 36 | Centennial | Colorado | Arrow Electronics | Wholesalers: Electronics and Office Equipment | 80112 | 1,297,674 |
| 37 | San Antonio | Texas | USAA | Insurance: Property and Casualty (Stock) | 78288 | 1,278,947 |
| 38 | Rosemont | Illinois | US Foods | Wholesalers: Food and Grocery | 60018 | 1,263,333 |
| 39 | Rosemead | California | Edison International | Utilities: Gas and Electric | 91770 | 1,257,143 |
| 40 | Corona | California | Monster Beverage | Beverages | 92879 | 1,250,000 |
| 41 | Medford | Oregon | Lithia Motors | Automotive Retailing, Services | 97501 | 1,211,921 |
| 42 | Herndon | Virginia | QXO Building Products | Wholesalers: Diversified | 20170 | 1,209,877 |
| 43 | Midland | Michigan | Dow | Chemicals | 48674 | 1,194,444 |
| 44 | Thousand Oaks | California | Amgen | Pharmaceuticals | 91320 | 1,192,857 |
| 45 | Chattanooga | Tennessee | Unum | Insurance: Life, Health (Stock) | 37402 | 1,183,486 |
| 46 | Northbrook | Illinois | Allstate | Insurance: Property and Casualty (Stock) | 60062 | 1,161,232 |
| 47 | Detroit | Michigan | General Motors | Motor Vehicles & Parts | 48265 | 1,156,790 |
| 48 | Mayfield Village | Ohio | Progressive | Insurance: Property and Casualty (Stock) | 44143 | 1,137,255 |
| 49 | Riverwoods | Illinois | Discover Financial | Diversified Financials | 60015 | 1,123,810 |
| 50 | Springfield | Massachusetts | Eversource Energy | Utilities: Gas and Electric | 01104 | 1,112,150 |
| 51 | Dearborn | Michigan | Ford Motor | Motor Vehicles & Parts | 48126 | 1,081,871 |
| 52 | Victor | New York | Constellation Brands | Beverages | 14564 | 1,075,269 |
| 53 | Redmond | Washington | Microsoft | Computer Software | 98052 | 1,075,000 |
| 54 | Fort Lauderdale | Florida | AutoNation | Automotive Retailing, Services | 33301 | 1,067,729 |
| 55 | Bloomfield Hills | Michigan | Penske Automotive | Automotive Retailing, Services | 48302 | 1,055,363 |
| 56 | Miami | Florida | Watsco | Wholesalers: Diversified | 33133 | 1,041,096 |
| 57 | North Chicago | Illinois | AbbVie | Pharmaceuticals | 60064 | 1,023,636 |
| 58 | Eden Prairie | Minnesota | UnitedHealth | Health Care: Insurance and Managed Care | 55344 | 1,000,750 |
| 59 | New Braunfels | Texas | Rush Enterprises | Automotive Retailing, Services | 78130 | 987,342 |
| 60 | New Orleans | Louisiana | Entergy | Utilities: Gas and Electric | 70113 | 967,480 |
| 61 | Tarrytown | New York | Regeneron Pharmaceuticals | Pharmaceuticals | 10591 | 940,397 |
| 62 | Moline | Illinois | Deere | Construction and Farm Machinery | 61265 | 931,532 |
| 63 | Palo Alto | California | HP | Computers, Office Equipment | 94304 | 924,138 |
| 64 | Orrville | Ohio | J.M. Smucker | Food Consumer Products | 44667 | 911,111 |
| 65 | Jackson | Michigan | CMS Energy | Utilities: Gas and Electric | 49201 | 903,614 |
| 66 | Round Rock | Texas | Dell Technologies | Computers, Office Equipment | 78682 | 885,185 |
| 67 | Rahway | New Jersey | Merck | Pharmaceuticals | 07065 | 867,568 |
| 68 | Scottsdale | Arizona | Reliance | Metals | 85254 | 862,500 |
| 69 | Oakland | California | PG&E | Utilities: Gas and Electric | 94612 | 859,155 |
| 70 | Fremont | California | Lam Research | Semiconductors and Other Electronic Components | 94538 | 856,322 |
| 71 | San Mateo | California | Franklin Resources | Securities | 94403 | 833,333 |
| 72 | Des Moines | Iowa | Principal Financial | Insurance: Life, Health (Stock) | 50392 | 817,259 |
| 73 | Westlake | Texas | Charles Schwab | Securities | 76262 | 809,969 |
| 74 | Newark | New Jersey | Public Service Enterprise | Utilities: Gas and Electric | 07102 | 792,308 |
| 75 | Tempe | Arizona | Carvana | Automotive Retailing, Services | 85281 | 787,356 |
| 76 | San Diego | California | Sempra | Utilities: Gas and Electric | 92101 | 785,714 |
| 77 | Indianapolis | Indiana | Corteva | Food Production | 46268 | 768,182 |
| 78 | Issaquah | Washington | Costco | General Merchandisers | 98027 | 764,264 |
| 79 | Oak Brook | Illinois | Ace Hardware | Wholesalers: Diversified | 60523 | 760,000 |
| 80 | Westminster | Colorado | Ball | Packaging, Containers | 80021 | 756,250 |
| 81 | Beverly Hills | California | Endeavor | Entertainment | 90210 | 750,000 |
| 82 | Evendale | Ohio | General Electric | Aerospace & Defense | 45215 | 730,189 |
| 83 | Summit | New Jersey | Kenvue | Household and Personal Products | 07901 | 704,545 |
| 84 | Mountain View | California | Intuit | Computer Software | 94043 | 673,554 |
| 85 | Kingsport | Tennessee | Eastman Chemical | Chemicals | 37660 | 671,429 |
| 86 | Sunny Isles Beach | Florida | Icahn Enterprises | Diversified Financials | 33160 | 666,667 |
| 87 | Camden | New Jersey | Campbell's | Food Consumer Products | 08103 | 666,667 |
| 88 | Plantation | Florida | Chewy | Internet Services and Retailing | 33322 | 661,111 |
| 89 | Westchester | Illinois | Ingredion | Food Production | 60154 | 660,714 |
| 90 | Merriam | Kansas | Seaboard | Food Production | 66202 | 650,000 |
| 91 | Milpitas | California | KLA | Semiconductors and Other Electronic Components | 95035 | 649,007 |
| 92 | Beaverton | Oregon | Nike | Apparel | 97005 | 647,355 |
| 93 | Richmond | Virginia | ARKO | Specialty Retailers: Other | 23227 | 644,068 |
| 94 | New Brunswick | New Jersey | Johnson & Johnson | Pharmaceuticals | 08933 | 643,012 |
| 95 | Byron Center | Michigan | SpartanNash | Wholesalers: Food and Grocery | 49315 | 633,333 |
| 96 | Buffalo | New York | M&T Bank | Commercial Banks | 14203 | 610,860 |
| 97 | Columbus | Ohio | Huntington Bancshares | Commercial Banks | 43287 | 603,015 |
| 98 | Manhattan Beach | California | Skechers U.S.A. | Apparel | 90266 | 596,026 |
| 99 | Austin | Minnesota | Hormel Foods | Food Consumer Products | 55912 | 595,000 |
| 100 | Hershey | Pennsylvania | Hershey | Food Consumer Products | 17033 | 580,311 |
| 101 | Oshkosh | Wisconsin | Oshkosh | Construction and Farm Machinery | 54902 | 578,378 |
| 102 | Parsippany | New Jersey | Avis Budget | Automotive Retailing, Services | 07054 | 575,610 |
| 103 | Bellevue | Washington | Expeditors International of Washington | Transportation and Logistics | 98006 | 560,847 |
| 104 | Redwood City | California | Electronic Arts | Entertainment | 94065 | 554,745 |
| 105 | Lake Forest | Illinois | Packaging Corp. of America | Packaging, Containers | 60045 | 545,455 |
| 106 | Allentown | Pennsylvania | Air Products & Chemicals | Chemicals | 18106 | 540,179 |
| 107 | Sunnyvale | California | Intuitive Surgical | Medical Products and Equipment | 94086 | 538,462 |
| 108 | Irving | Texas | Kimberly-Clark | Household and Personal Products | 75038 | 528,947 |
| 109 | Omaha | Nebraska | Peter Kiewit Sons' | Engineering & Construction | 68102 | 528,302 |
| 110 | Englewood | Colorado | QVC | Internet Services and Retailing | 80112 | 526,316 |
| 111 | Monroe | Louisiana | Lumen Technologies | Telecommunications | 71203 | 524,000 |
| 112 | Burlington | Massachusetts | Keurig Dr Pepper | Beverages | 01803 | 523,810 |
| 113 | Palm Beach Gardens | Florida | Carrier Global | Industrial Machinery | 33418 | 516,667 |
| 114 | Wilmington | Delaware | DuPont | Chemicals | 19805 | 516,667 |
| 115 | Tampa | Florida | Crown s | Packaging, Containers | 33637 | 513,043 |
| 116 | Melville | New York | Henry Schein | Wholesalers: Health Care | 11747 | 508,000 |
| 117 | Spring | Texas | Hewlett Packard | Computers, Office Equipment | 77389 | 493,443 |
| 118 | Columbus | Indiana | Cummins | Industrial Machinery | 47201 | 489,943 |
| 119 | Richfield | Minnesota | Best Buy | Specialty Retailers: Other | 55423 | 488,235 |
| 120 | Duluth | Georgia | AGCO | Construction and Farm Machinery | 30096 | 487,500 |
| 121 | Birmingham | Alabama | Regions Financial | Commercial Banks | 35203 | 479,592 |
| 122 | Long Island City | New York | JetBlue Airways | Airlines | 11101 | 469,697 |
| 123 | Glen Allen | Virginia | Owens & Minor | Wholesalers: Health Care | 23060 | 461,207 |
| 124 | Canonsburg | Pennsylvania | Viatris | Pharmaceuticals | 15317 | 459,375 |
| 125 | Stamford | Connecticut | Philip Morris | Tobacco | 06901 | 456,077 |
| 126 | Cambridge | Massachusetts | GE Vernova | Energy | 02141 | 454,427 |
| 127 | Melbourne | Florida | L3Harris Technologies | Aerospace & Defense | 32919 | 453,191 |
| 128 | Warsaw | Indiana | Zimmer Biomet s | Medical Products and Equipment | 46580 | 452,941 |
| 129 | Ankeny | Iowa | Casey's General Stores | Specialty Retailers: Other | 50021 | 450,151 |
| 130 | Elkhart | Indiana | THOR Industries | Motor Vehicles & Parts | 46514 | 448,430 |
| 131 | Burbank | California | Walt Disney | Entertainment | 91521 | 445,854 |
| 132 | Toledo | Ohio | Owens Corning | Building Materials, Glass | 43659 | 440,000 |
| 133 | Livonia | Michigan | Masco | Home Equipment, Furnishings | 48152 | 433,333 |
| 134 | Portage | Michigan | Stryker | Medical Products and Equipment | 49002 | 426,415 |
| 135 | Falls Church | Virginia | Northrop Grumman | Aerospace & Defense | 22042 | 422,680 |
| 136 | Boston | Massachusetts | State Street | Commercial Banks | 02114 | 420,152 |
| 137 | Santa Clara | California | ServiceNow | Computer Software | 95054 | 418,251 |
| 138 | Pleasanton | California | Workday | Computer Software | 94588 | 409,756 |
| 139 | Fort Worth | Texas | American Airlines | Airlines | 76155 | 406,602 |
| 140 | Providence | Rhode Island | Textron | Aerospace & Defense | 02903 | 402,941 |
| 141 | Boise | Idaho | Albertsons | Food & Drug Stores | 83706 | 402,848 |
| 142 | Deerfield | Illinois | Baxter International | Medical Products and Equipment | 60015 | 397,368 |
| 143 | Wilmington | Massachusetts | Analog Devices | Semiconductors and Other Electronic Components | 01887 | 391,667 |
| 144 | Mooresville | North Carolina | Lowe's | Specialty Retailers: Other | 28117 | 388,399 |
| 145 | Arlington | Virginia | Boeing | Aerospace & Defense | 22202 | 386,628 |
| 146 | Springdale | Arkansas | Tyson Foods | Food Production | 72762 | 386,232 |
| 147 | Brentwood | Tennessee | Tractor Supply | Specialty Retailers: Other | 37027 | 382,051 |
| 148 | Charlotte | North Carolina | Honeywell | Industrial Machinery | 28202 | 377,451 |
| 149 | Benton Harbor | Michigan | Whirlpool | Electronics, Electrical Equip. | 49022 | 377,273 |
| 150 | Maplewood | Minnesota | Solventum | Medical Products and Equipment | 55144 | 377,273 |
| 151 | Washington | District of Columbia | Xylem | Industrial Machinery | 20003 | 373,913 |
| 152 | Abbott Park | Illinois | Abbott Laboratories | Medical Products and Equipment | 60064 | 368,421 |
| 153 | Norwalk | Connecticut | EMCOR | Engineering & Construction | 06851 | 361,386 |
| 154 | Glenview | Illinois | Illinois Tool Works | Industrial Machinery | 60025 | 361,364 |
| 155 | Lowell | Arkansas | J.B. Hunt Transport Services | Trucking, Truck Leasing | 72745 | 360,119 |
| 156 | Coraopolis | Pennsylvania | Dick's Sporting Goods | Specialty Retailers: Other | 15108 | 358,289 |
| 157 | Winona | Minnesota | Fastenal | Wholesalers: Diversified | 55987 | 357,143 |
| 158 | Downers Grove | Illinois | Dover | Industrial Machinery | 60515 | 350,000 |
| 159 | Estero | Florida | Hertz | Automotive Retailing, Services | 33928 | 346,154 |
| 160 | Waltham | Massachusetts | Thermo Fisher Scientific | Scientific, Photographic and Control Equipment | 02451 | 343,200 |
| 161 | Chandler | Arizona | Microchip Technology | Semiconductors and Other Electronic Components | 85224 | 340,807 |
| 162 | Austin | Texas | Oracle | Computer Software | 78741 | 333,333 |
| 163 | St. Paul | Minnesota | Ecolab | Chemicals | 55102 | 327,083 |
| 164 | Cleveland | Ohio | Parker-Hannifin | Industrial Machinery | 44124 | 325,696 |
| 165 | Bentonville | Arkansas | Walmart | General Merchandisers | 72712 | 324,286 |
| 166 | New Britain | Connecticut | Stanley Black & Decker | Industrial Machinery | 06053 | 317,526 |
| 167 | Marlborough | Massachusetts | Boston Scientific | Medical Products and Equipment | 01752 | 315,094 |
| 168 | Reston | Virginia | Science Applications International | Information Technology Services | 20190 | 312,500 |
| 169 | Pittsburgh | Pennsylvania | Howmet Aerospace | Aerospace & Defense | 15212 | 309,623 |
| 170 | Milwaukee | Wisconsin | Rockwell Automation | Electronics, Electrical Equip. | 53204 | 307,407 |
| 171 | Antioch | Tennessee | LKQ | Wholesalers: Diversified | 37013 | 306,383 |
| 172 | Roseland | New Jersey | Automatic Data Processing | Diversified Outsourcing Services | 07068 | 300,000 |
| 173 | Des Peres | Missouri | Edward Jones | Securities | 63131 | 296,364 |
| 174 | Evansville | Indiana | Berry Global | Packaging, Containers | 47710 | 292,857 |
| 175 | Bolingbrook | Illinois | Ulta Beauty | Specialty Retailers: Other | 60440 | 289,744 |
| 176 | Purchase | New York | PepsiCo | Food Consumer Products | 10577 | 288,088 |
| 177 | Akron | Ohio | Goodyear Tire & Rubber | Motor Vehicles & Parts | 44316 | 277,941 |
| 178 | Franklin Lakes | New Jersey | Becton Dickinson | Medical Products and Equipment | 07417 | 272,973 |
| 179 | Sumner | Washington | Lululemon athletica | Specialty Retailers: Apparel | 98390 | 271,795 |
| 180 | Menomonee Falls | Wisconsin | Kohl's | General Merchandisers | 53051 | 270,000 |
| 181 | Newport News | Virginia | Huntington Ingalls Industries | Aerospace & Defense | 23607 | 261,364 |
| 182 | Nashville | Tennessee | HCA Healthcare | Health Care: Medical Facilities | 37203 | 260,517 |
| 183 | Maumee | Ohio | Dana | Motor Vehicles & Parts | 43537 | 260,101 |
| 184 | Westerville | Ohio | Vertiv s | Electronics, Electrical Equip. | 43082 | 258,065 |
| 185 | Calhoun | Georgia | Mohawk Industries | Home Equipment, Furnishings | 30701 | 257,757 |
| 186 | Mentor | Ohio | Avery Dennison | Packaging, Containers | 44060 | 251,429 |
| 187 | Las Vegas | Nevada | MGM Resorts International | Hotels, Casinos, Resorts | 89109 | 249,275 |
| 188 | Coral Gables | Florida | Ryder System | Transportation and Logistics | 33134 | 248,521 |
| 189 | Atlanta | Georgia | UPS | Mail, Package and Freight Delivery | 30328 | 244,761 |
| 190 | Minneapolis | Minnesota | Target | General Merchandisers | 55403 | 242,273 |
| 191 | Dallas | Texas | Tenet Healthcare | Health Care: Medical Facilities | 75254 | 240,139 |
| 192 | Franklin | Tennessee | Community Health Systems | Health Care: Medical Facilities | 37067 | 240,000 |
| 193 | St. Louis | Missouri | Emerson Electric | Industrial Machinery | 63136 | 239,726 |
| 194 | Louisville | Kentucky | Yum Brands | Food Services | 40213 | 236,593 |
| 195 | Lakeland | Florida | Publix Super Markets | Food & Drug Stores | 33811 | 236,078 |
| 196 | Corning | New York | Corning | Electronics, Electrical Equip. | 14831 | 232,682 |
| 197 | Raleigh | North Carolina | Advance Auto Parts | Specialty Retailers: Other | 27609 | 227,083 |
| 198 | Reno | Nevada | Caesars Entertainment | Hotels, Casinos, Resorts | 89501 | 226,000 |
| 199 | Burlington | New Jersey | Burlington Stores | Specialty Retailers: Apparel | 08016 | 224,101 |
| 200 | Armonk | New York | IBM | Information Technology Services | 10504 | 220,738 |
| 201 | Chesapeake | Virginia | Dollar Tree | Specialty Retailers: Other | 23320 | 220,630 |
| 202 | San Jose | California | Sanmina | Semiconductors and Other Electronic Components | 95134 | 220,290 |
| 203 | Phoenix | Arizona | Sprouts Farmers Market | Food & Drug Stores | 85054 | 220,000 |
| 204 | Jacksonville | Florida | Fidelity National Information | Financial Data Services | 32202 | 210,000 |
| 205 | St. Petersburg | Florida | Jabil | Semiconductors and Other Electronic Components | 33716 | 209,420 |
| 206 | Goodlettsville | Tennessee | Dollar General | Specialty Retailers: Other | 37072 | 209,063 |
| 207 | Rolling Meadows | Illinois | Arthur J. Gallagher | Diversified Financials | 60008 | 207,143 |
| 208 | Cincinnati | Ohio | Cintas | Diversified Outsourcing Services | 45262 | 206,452 |
| 209 | Houston | Texas | KBR | Information Technology Services | 77002 | 202,632 |
| 210 | Burlington | North Carolina | Labcorp s | Health Care: Pharmacy and Other Services | 27215 | 198,777 |
| 211 | Farmington | Connecticut | Otis Worldwide | Industrial Machinery | 06032 | 198,611 |
| 212 | Dublin | California | Ross Stores | Specialty Retailers: Apparel | 94568 | 197,196 |
| 213 | Secaucus | New Jersey | Quest Diagnostics | Health Care: Pharmacy and Other Services | 07094 | 196,040 |
| 214 | Springfield | Missouri | O'Reilly Automotive | Specialty Retailers: Other | 65802 | 195,093 |
| 215 | San Francisco | California | Gap | Specialty Retailers: Apparel | 94105 | 184,146 |
| 216 | Memphis | Tennessee | AutoZone | Specialty Retailers: Other | 38103 | 183,532 |
| 217 | King of Prussia | Pennsylvania | Universal Health Services | Health Care: Medical Facilities | 19406 | 180,571 |
| 218 | Durham | North Carolina | IQVIA s | Health Care: Pharmacy and Other Services | 27703 | 175,000 |
| 219 | Chicago | Illinois | McDonald's | Food Services | 60607 | 172,667 |
| 220 | Denver | Colorado | DaVita | Health Care: Medical Facilities | 80202 | 168,421 |
| 221 | Auburn Hills | Michigan | Autoliv | Motor Vehicles & Parts | 48326 | 166,934 |
| 222 | Bethesda | Maryland | Marriott International | Hotels, Casinos, Resorts | 20814 | 161,935 |
| 223 | Framingham | Massachusetts | TJX | Specialty Retailers: Apparel | 01701 | 154,945 |
| 224 | Southfield | Michigan | Lear | Motor Vehicles & Parts | 48033 | 134,139 |
| 225 | Wallingford | Connecticut | Amphenol | Network and Other Communications Equipment | 06492 | 121,600 |
| 226 | Ashburn | Virginia | DXC Technology | Information Technology Services | 20147 | 105,385 |
| 227 | Seattle | Washington | Starbucks | Food Services | 98134 | 100,277 |
| 228 | Greenwich | Connecticut | GXO Logistics | Transportation and Logistics | 06831 | 91,051 |
| 229 | Newport Beach | California | Chipotle Mexican Grill | Food Services | 92660 | 86,590 |
| 230 | New York | New York | ABM Industries | Diversified Outsourcing Services | 10006 | 71,795 |
| 231 | Philadelphia | Pennsylvania | Aramark | Diversified Outsourcing Services | 19103 | 65,242 |
| 232 | McLean | Virginia | Hilton | Hotels, Casinos, Resorts | 22102 | 61,878 |
| 233 | Orlando | Florida | Darden Restaurants | Food Services | 32837 | 59,655 |
| 234 | Teaneck | New Jersey | Cognizant Technology | Information Technology Services | 07666 | 58,492 |
| 235 | Plano | Texas | Yum China s | Food Services | 75074 | 46,029 |
| 236 | Newark | California | Concentrix | Information Technology Services | 94560 | 21,333 |
In [195]:
# Join the Dataframe 'gdfusact' with 'dfctmineffco' for the Top 10
gdfusactmineffco = gdfusact.merge(dfctmineffco, how = 'inner', on = ['Zip Code'])
gdfusactmineffco = gdfusactmineffco.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [196]:
mctmineffco = gdfusactmineffco.explore(column='Efficiency', name='The Least Efficient Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmineffco)
mctmineffco
Out[196]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [197]:
# Check the Average Efficiency in each City
dfctavreff = df.head(1)
dfctavreff.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for ct in ctslist[0:]:
dfct = df.where(df['City'] == ct[0]).dropna().where(df['State'] == ct[1]).dropna()
dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
#print(dfct.groupby(['State','City'], as_index=False).mean('Efficiency'))
dfctavreff = pd.concat([dfctavreff, dfct.groupby(['State','City'], as_index=False).mean('Efficiency')], ignore_index=True)[['State','City','Efficiency']]
dfctavreff = dfctavreff.drop(0)
dfctavreff.sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[197]:
| State | City | Efficiency | |
|---|---|---|---|
| 0 | California | El Segundo | 19,400,000 |
| 1 | Ohio | Findlay | 7,672,131 |
| 2 | Oklahoma | Oklahoma City | 6,913,043 |
| 3 | Texas | San Antonio | 6,902,100 |
| 4 | Pennsylvania | Conshohocken | 6,681,818 |
| 5 | District of Columbia | Washington | 6,460,449 |
| 6 | Ohio | Toledo | 5,934,286 |
| 7 | Texas | Midland | 5,550,000 |
| 8 | Missouri | Chesterfield | 5,390,244 |
| 9 | Ohio | Dublin | 4,685,950 |
| 10 | Florida | Miami | 4,227,158 |
| 11 | Virginia | McLean | 4,118,383 |
| 12 | Minnesota | Inver Grove Heights | 3,672,897 |
| 13 | Texas | Houston | 3,515,320 |
| 14 | Connecticut | Bloomfield | 3,412,983 |
| 15 | Tennessee | Brentwood | 3,316,026 |
| 16 | New Jersey | Parsippany | 3,245,567 |
| 17 | Texas | Spring | 3,117,000 |
| 18 | Oklahoma | Tulsa | 2,991,711 |
| 19 | California | Los Gatos | 2,785,714 |
| 20 | Ohio | Maumee | 2,586,572 |
| 21 | Texas | Arlington | 2,486,486 |
| 22 | Massachusetts | Springfield | 2,480,182 |
| 23 | Massachusetts | Waltham | 2,434,758 |
| 24 | California | Cupertino | 2,384,146 |
| 25 | California | Long Beach | 2,255,556 |
| 26 | California | Menlo Park | 2,219,973 |
| 27 | Pennsylvania | Fort Washington | 2,204,082 |
| 28 | Michigan | Lansing | 2,164,384 |
| 29 | Ohio | Fairfield | 2,017,857 |
| 30 | New York | New York | 2,015,087 |
| 31 | Pennsylvania | Erie | 1,970,149 |
| 32 | Wisconsin | Madison | 1,918,919 |
| 33 | California | Newport Beach | 1,880,504 |
| 34 | Pennsylvania | Radnor | 1,877,551 |
| 35 | California | Irvine | 1,839,080 |
| 36 | Illinois | Bloomington | 1,824,926 |
| 37 | Minnesota | Arden Hills | 1,800,000 |
| 38 | Colorado | Denver | 1,799,566 |
| 39 | Arizona | Scottsdale | 1,797,917 |
| 40 | Rhode Island | Johnston | 1,793,103 |
| 41 | Maryland | Baltimore | 1,661,972 |
| 42 | California | Foster City | 1,636,364 |
| 43 | Texas | Irving | 1,585,504 |
| 44 | California | Woodland Hills | 1,565,657 |
| 45 | California | Fremont | 1,561,882 |
| 46 | Wisconsin | Milwaukee | 1,558,929 |
| 47 | Arkansas | El Dorado | 1,543,103 |
| 48 | Virginia | Richmond | 1,492,470 |
| 49 | Texas | Dallas | 1,489,891 |
| 50 | Georgia | Columbus | 1,488,189 |
| 51 | California | Oakland | 1,486,595 |
| 52 | Florida | Juno Beach | 1,476,190 |
| 53 | Ohio | Columbus | 1,472,016 |
| 54 | Rhode Island | Woonsocket | 1,436,609 |
| 55 | New Jersey | Princeton | 1,416,422 |
| 56 | Illinois | Vernon Hills | 1,390,728 |
| 57 | Connecticut | Hartford | 1,387,435 |
| 58 | Massachusetts | Boston | 1,361,465 |
| 59 | Ohio | Cincinnati | 1,354,012 |
| 60 | Indiana | Fort Wayne | 1,346,154 |
| 61 | Michigan | Detroit | 1,335,097 |
| 62 | New Jersey | Newark | 1,324,914 |
| 63 | Colorado | Centennial | 1,297,674 |
| 64 | California | Mountain View | 1,291,496 |
| 65 | Illinois | Rosemont | 1,263,333 |
| 66 | California | Rosemead | 1,257,143 |
| 67 | Connecticut | Greenwich | 1,252,711 |
| 68 | California | Corona | 1,250,000 |
| 69 | Missouri | St. Louis | 1,216,159 |
| 70 | Oregon | Medford | 1,211,921 |
| 71 | Virginia | Herndon | 1,209,877 |
| 72 | Michigan | Midland | 1,194,444 |
| 73 | California | Thousand Oaks | 1,192,857 |
| 74 | Tennessee | Chattanooga | 1,183,486 |
| 75 | California | Palo Alto | 1,170,177 |
| 76 | Illinois | Northbrook | 1,161,232 |
| 77 | Indiana | Indianapolis | 1,144,158 |
| 78 | Minnesota | Eden Prairie | 1,141,679 |
| 79 | Ohio | Mayfield Village | 1,137,255 |
| 80 | Illinois | Riverwoods | 1,123,810 |
| 81 | California | Santa Clara | 1,122,844 |
| 82 | Nebraska | Omaha | 1,116,963 |
| 83 | Minnesota | Minneapolis | 1,108,596 |
| 84 | Michigan | Dearborn | 1,081,871 |
| 85 | New York | Victor | 1,075,269 |
| 86 | Washington | Redmond | 1,075,000 |
| 87 | Florida | Fort Lauderdale | 1,067,729 |
| 88 | Michigan | Bloomfield Hills | 1,055,363 |
| 89 | Illinois | North Chicago | 1,023,636 |
| 90 | California | San Francisco | 1,023,212 |
| 91 | Texas | New Braunfels | 987,342 |
| 92 | California | San Diego | 986,470 |
| 93 | Louisiana | New Orleans | 967,480 |
| 94 | California | San Jose | 943,023 |
| 95 | New York | Tarrytown | 940,397 |
| 96 | Illinois | Moline | 931,532 |
| 97 | Ohio | Orrville | 911,111 |
| 98 | Pennsylvania | Allentown | 904,418 |
| 99 | Michigan | Jackson | 903,614 |
| 100 | North Carolina | Charlotte | 891,162 |
| 101 | Texas | Round Rock | 885,185 |
| 102 | New Jersey | Rahway | 867,568 |
| 103 | Massachusetts | Cambridge | 865,371 |
| 104 | California | Beverly Hills | 854,339 |
| 105 | Washington | Bellevue | 840,224 |
| 106 | Colorado | Englewood | 839,800 |
| 107 | California | San Mateo | 833,333 |
| 108 | Iowa | Des Moines | 817,259 |
| 109 | Georgia | Duluth | 817,083 |
| 110 | Florida | Jacksonville | 813,394 |
| 111 | Texas | Westlake | 809,969 |
| 112 | Arizona | Tempe | 787,356 |
| 113 | Kentucky | Louisville | 778,332 |
| 114 | Washington | Issaquah | 764,264 |
| 115 | Illinois | Oak Brook | 760,000 |
| 116 | Arizona | Phoenix | 757,793 |
| 117 | Colorado | Westminster | 756,250 |
| 118 | Rhode Island | Providence | 738,370 |
| 119 | Minnesota | St. Paul | 730,456 |
| 120 | Ohio | Evendale | 730,189 |
| 121 | Virginia | Arlington | 724,049 |
| 122 | Georgia | Atlanta | 711,349 |
| 123 | New Jersey | Summit | 704,545 |
| 124 | Connecticut | Stamford | 699,383 |
| 125 | Illinois | Chicago | 677,019 |
| 126 | Tennessee | Kingsport | 671,429 |
| 127 | Connecticut | Norwalk | 670,362 |
| 128 | Ohio | Akron | 667,426 |
| 129 | New Jersey | Camden | 666,667 |
| 130 | Florida | Sunny Isles Beach | 666,667 |
| 131 | Florida | Plantation | 661,111 |
| 132 | Illinois | Westchester | 660,714 |
| 133 | Florida | Tampa | 658,696 |
| 134 | Kansas | Merriam | 650,000 |
| 135 | California | Milpitas | 649,007 |
| 136 | New York | Long Island City | 647,693 |
| 137 | Oregon | Beaverton | 647,355 |
| 138 | New Jersey | New Brunswick | 643,012 |
| 139 | Michigan | Byron Center | 633,333 |
| 140 | Pennsylvania | Pittsburgh | 618,757 |
| 141 | Illinois | Lake Forest | 616,727 |
| 142 | New York | Buffalo | 610,860 |
| 143 | Virginia | Glen Allen | 607,876 |
| 144 | California | Redwood City | 597,225 |
| 145 | California | Manhattan Beach | 596,026 |
| 146 | Minnesota | Austin | 595,000 |
| 147 | Virginia | Reston | 583,503 |
| 148 | Pennsylvania | Hershey | 580,311 |
| 149 | Wisconsin | Oshkosh | 578,378 |
| 150 | Texas | Austin | 555,290 |
| 151 | Virginia | Newport News | 553,539 |
| 152 | Alabama | Birmingham | 548,129 |
| 153 | North Carolina | Raleigh | 547,068 |
| 154 | New York | Purchase | 543,477 |
| 155 | California | Sunnyvale | 538,462 |
| 156 | Louisiana | Monroe | 524,000 |
| 157 | Massachusetts | Burlington | 523,810 |
| 158 | Delaware | Wilmington | 516,667 |
| 159 | Florida | Palm Beach Gardens | 516,667 |
| 160 | New York | Melville | 508,000 |
| 161 | Florida | St. Petersburg | 496,815 |
| 162 | Illinois | Deerfield | 491,159 |
| 163 | Indiana | Columbus | 489,943 |
| 164 | Minnesota | Richfield | 488,235 |
| 165 | Arizona | Chandler | 474,599 |
| 166 | Ohio | Cleveland | 470,144 |
| 167 | Massachusetts | Marlborough | 468,153 |
| 168 | Idaho | Boise | 462,883 |
| 169 | Pennsylvania | Canonsburg | 459,375 |
| 170 | Florida | Melbourne | 453,191 |
| 171 | Indiana | Warsaw | 452,941 |
| 172 | Iowa | Ankeny | 450,151 |
| 173 | Indiana | Elkhart | 448,430 |
| 174 | California | Burbank | 445,854 |
| 175 | Michigan | Livonia | 433,333 |
| 176 | Michigan | Portage | 426,415 |
| 177 | Virginia | Falls Church | 422,680 |
| 178 | California | Pleasanton | 409,756 |
| 179 | Texas | Fort Worth | 406,602 |
| 180 | Washington | Seattle | 398,315 |
| 181 | Massachusetts | Wilmington | 391,667 |
| 182 | North Carolina | Mooresville | 388,399 |
| 183 | Arkansas | Springdale | 386,232 |
| 184 | Minnesota | Maplewood | 377,273 |
| 185 | Michigan | Benton Harbor | 377,273 |
| 186 | Maryland | Bethesda | 374,356 |
| 187 | Pennsylvania | Philadelphia | 372,456 |
| 188 | Illinois | Abbott Park | 368,421 |
| 189 | Illinois | Glenview | 361,364 |
| 190 | Arkansas | Lowell | 360,119 |
| 191 | Pennsylvania | Coraopolis | 358,289 |
| 192 | Minnesota | Winona | 357,143 |
| 193 | Illinois | Downers Grove | 350,000 |
| 194 | Florida | Estero | 346,154 |
| 195 | Arkansas | Bentonville | 324,286 |
| 196 | Connecticut | New Britain | 317,526 |
| 197 | Florida | Coral Gables | 316,448 |
| 198 | Tennessee | Antioch | 306,383 |
| 199 | New Jersey | Roseland | 300,000 |
| 200 | Tennessee | Memphis | 298,002 |
| 201 | Missouri | Des Peres | 296,364 |
| 202 | Indiana | Evansville | 292,857 |
| 203 | Illinois | Bolingbrook | 289,744 |
| 204 | New Jersey | Franklin Lakes | 272,973 |
| 205 | Washington | Sumner | 271,795 |
| 206 | Wisconsin | Menomonee Falls | 270,000 |
| 207 | Michigan | Auburn Hills | 267,540 |
| 208 | Nevada | Las Vegas | 265,535 |
| 209 | Tennessee | Nashville | 260,517 |
| 210 | Ohio | Westerville | 258,065 |
| 211 | Georgia | Calhoun | 257,757 |
| 212 | Ohio | Mentor | 251,429 |
| 213 | Tennessee | Franklin | 240,000 |
| 214 | Florida | Lakeland | 236,078 |
| 215 | New York | Corning | 232,682 |
| 216 | Nevada | Reno | 226,000 |
| 217 | New Jersey | Burlington | 224,101 |
| 218 | New York | Armonk | 220,738 |
| 219 | Virginia | Chesapeake | 220,630 |
| 220 | Tennessee | Goodlettsville | 209,063 |
| 221 | Illinois | Rolling Meadows | 207,143 |
| 222 | North Carolina | Burlington | 198,777 |
| 223 | Connecticut | Farmington | 198,611 |
| 224 | California | Dublin | 197,196 |
| 225 | New Jersey | Secaucus | 196,040 |
| 226 | Missouri | Springfield | 195,093 |
| 227 | Pennsylvania | King of Prussia | 180,571 |
| 228 | North Carolina | Durham | 175,000 |
| 229 | Massachusetts | Framingham | 154,945 |
| 230 | Michigan | Southfield | 134,139 |
| 231 | Connecticut | Wallingford | 121,600 |
| 232 | Virginia | Ashburn | 105,385 |
| 233 | Florida | Orlando | 59,655 |
| 234 | New Jersey | Teaneck | 58,492 |
| 235 | Texas | Plano | 46,029 |
| 236 | California | Newark | 21,333 |
In [ ]:
In [198]:
# Join the Dataframe 'gdfusact' with 'dfctavreff' for the Top 10
dfctavreff = dfctavreff.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfctavreff
Out[198]:
| State | City | Efficiency | Company | Zip Code | |
|---|---|---|---|---|---|
| 0 | California | El Segundo | 19,400,000 | A-Mark Precious Metals | 90245 |
| 1 | Ohio | Findlay | 7,672,131 | Marathon Petroleum | 45840 |
| 2 | Oklahoma | Oklahoma City | 6,913,043 | Devon Energy | 73102 |
| 3 | Texas | San Antonio | 6,902,100 | USAA | 78288 |
| 4 | Texas | San Antonio | 6,902,100 | Valero Energy | 78249 |
| 5 | Pennsylvania | Conshohocken | 6,681,818 | Cencora | 19428 |
| 6 | District of Columbia | Washington | 6,460,449 | Xylem | 20003 |
| 7 | District of Columbia | Washington | 6,460,449 | Danaher | 20037 |
| 8 | District of Columbia | Washington | 6,460,449 | Fannie Mae | 20005 |
| 9 | Ohio | Toledo | 5,934,286 | Welltower | 43615 |
| 10 | Ohio | Toledo | 5,934,286 | Owens Corning | 43659 |
| 11 | Texas | Midland | 5,550,000 | Diamondback Energy | 79701 |
| 12 | Missouri | Chesterfield | 5,390,244 | Reinsurance of America | 63017 |
| 13 | Ohio | Dublin | 4,685,950 | Cardinal Health | 43017 |
| 14 | Florida | Miami | 4,227,158 | World Kinect | 33178 |
| 15 | Florida | Miami | 4,227,158 | Watsco | 33133 |
| 16 | Florida | Miami | 4,227,158 | Lennar | 33126 |
| 17 | Virginia | McLean | 4,118,383 | Freddie Mac | 22102 |
| 18 | Virginia | McLean | 4,118,383 | Capital One | 22102 |
| 19 | Virginia | McLean | 4,118,383 | Hilton | 22102 |
| 20 | Virginia | McLean | 4,118,383 | Booz Allen Hamilton | 22102 |
| 21 | Minnesota | Inver Grove Heights | 3,672,897 | CHS | 55077 |
| 22 | Texas | Houston | 3,515,320 | Waste Management | 77002 |
| 23 | Texas | Houston | 3,515,320 | Kinder Morgan | 77002 |
| 24 | Texas | Houston | 3,515,320 | Corebridge Financial | 77019 |
| 25 | Texas | Houston | 3,515,320 | Targa Resources | 77002 |
| 26 | Texas | Houston | 3,515,320 | Cheniere Energy | 77002 |
| 27 | Texas | Houston | 3,515,320 | KBR | 77002 |
| 28 | Texas | Houston | 3,515,320 | Westlake | 77056 |
| 29 | Texas | Houston | 3,515,320 | APA | 77042 |
| 30 | Texas | Houston | 3,515,320 | NOV | 77042 |
| 31 | Texas | Houston | 3,515,320 | CenterPoint Energy | 77002 |
| 32 | Texas | Houston | 3,515,320 | Par Pacific | 77024 |
| 33 | Texas | Houston | 3,515,320 | Quanta Services | 77008 |
| 34 | Texas | Houston | 3,515,320 | Halliburton | 77032 |
| 35 | Texas | Houston | 3,515,320 | 1 Automotive | 77024 |
| 36 | Texas | Houston | 3,515,320 | EOG Resources | 77002 |
| 37 | Texas | Houston | 3,515,320 | Enterprise Products Partners | 77002 |
| 38 | Texas | Houston | 3,515,320 | Chevron | 77002 |
| 39 | Texas | Houston | 3,515,320 | Phillips 66 | 77042 |
| 40 | Texas | Houston | 3,515,320 | Occidental Petroleum | 77046 |
| 41 | Texas | Houston | 3,515,320 | Sysco | 77077 |
| 42 | Texas | Houston | 3,515,320 | Baker Hughes | 77079 |
| 43 | Texas | Houston | 3,515,320 | NRG Energy | 77002 |
| 44 | Texas | Houston | 3,515,320 | Plains GP | 77002 |
| 45 | Texas | Houston | 3,515,320 | ConocoPhillips | 77079 |
| 46 | Connecticut | Bloomfield | 3,412,983 | Cigna | 06002 |
| 47 | Tennessee | Brentwood | 3,316,026 | Tractor Supply | 37027 |
| 48 | Tennessee | Brentwood | 3,316,026 | Delek US | 37027 |
| 49 | New Jersey | Parsippany | 3,245,567 | Avis Budget | 07054 |
| 50 | New Jersey | Parsippany | 3,245,567 | PBF Energy | 07054 |
| 51 | New Jersey | Parsippany | 3,245,567 | Zoetis | 07054 |
| 52 | Texas | Spring | 3,117,000 | Exxon Mobil | 77389 |
| 53 | Texas | Spring | 3,117,000 | Hewlett Packard | 77389 |
| 54 | Oklahoma | Tulsa | 2,991,711 | Williams | 74172 |
| 55 | Oklahoma | Tulsa | 2,991,711 | Oneok | 74103 |
| 56 | California | Los Gatos | 2,785,714 | Netflix | 95032 |
| 57 | Ohio | Maumee | 2,586,572 | Andersons | 43537 |
| 58 | Ohio | Maumee | 2,586,572 | Dana | 43537 |
| 59 | Texas | Arlington | 2,486,486 | D.R. Horton | 76011 |
| 60 | Massachusetts | Springfield | 2,480,182 | Eversource Energy | 01104 |
| 61 | Massachusetts | Springfield | 2,480,182 | Mass Mutual | 01111 |
| 62 | Massachusetts | Waltham | 2,434,758 | Thermo Fisher Scientific | 02451 |
| 63 | Massachusetts | Waltham | 2,434,758 | Global Partners | 02453 |
| 64 | California | Cupertino | 2,384,146 | Apple | 95014 |
| 65 | California | Long Beach | 2,255,556 | Molina Healthcare | 90802 |
| 66 | California | Menlo Park | 2,219,973 | Meta | 94025 |
| 67 | Pennsylvania | Fort Washington | 2,204,082 | Toll Brothers | 19034 |
| 68 | Michigan | Lansing | 2,164,384 | Auto-Owners Insurance | 48917 |
| 69 | Ohio | Fairfield | 2,017,857 | Cincinnati Financial | 45014 |
| 70 | New York | New York | 2,015,087 | Citi | 10013 |
| 71 | New York | New York | 2,015,087 | Verizon | 10036 |
| 72 | New York | New York | 2,015,087 | Goldman Sachs | 10282 |
| 73 | New York | New York | 2,015,087 | Morgan Stanley | 10036 |
| 74 | New York | New York | 2,015,087 | American Express | 10285 |
| 75 | New York | New York | 2,015,087 | StoneX | 10169 |
| 76 | New York | New York | 2,015,087 | JPMorgan Chase | 10017 |
| 77 | New York | New York | 2,015,087 | MetLife | 10166 |
| 78 | New York | New York | 2,015,087 | PVH | 10017 |
| 79 | New York | New York | 2,015,087 | Omnicom | 10017 |
| 80 | New York | New York | 2,015,087 | Estée Lauder | 10153 |
| 81 | New York | New York | 2,015,087 | Interpublic | 10022 |
| 82 | New York | New York | 2,015,087 | Foot Locker | 10001 |
| 83 | New York | New York | 2,015,087 | Consolidated Edison | 10003 |
| 84 | New York | New York | 2,015,087 | S&P Global | 10041 |
| 85 | New York | New York | 2,015,087 | Voya Financial | 10169 |
| 86 | New York | New York | 2,015,087 | ABM Industries | 10006 |
| 87 | New York | New York | 2,015,087 | Sirius XM | 10020 |
| 88 | New York | New York | 2,015,087 | Guardian Life | 10001 |
| 89 | New York | New York | 2,015,087 | Oscar Health | 10013 |
| 90 | New York | New York | 2,015,087 | Pfizer | 10001 |
| 91 | New York | New York | 2,015,087 | News Corp. | 10036 |
| 92 | New York | New York | 2,015,087 | Jefferies Financial | 10022 |
| 93 | New York | New York | 2,015,087 | Fox | 10036 |
| 94 | New York | New York | 2,015,087 | Blackstone | 10154 |
| 95 | New York | New York | 2,015,087 | Hess | 10036 |
| 96 | New York | New York | 2,015,087 | Equitable | 10105 |
| 97 | New York | New York | 2,015,087 | Kyndryl s | 10017 |
| 98 | New York | New York | 2,015,087 | International Flavors & Fragrances | 10019 |
| 99 | New York | New York | 2,015,087 | Loews | 10019 |
| 100 | New York | New York | 2,015,087 | Paramount Global | 10036 |
| 101 | New York | New York | 2,015,087 | Colgate-Palmolive | 10022 |
| 102 | New York | New York | 2,015,087 | BlackRock | 10001 |
| 103 | New York | New York | 2,015,087 | Macy's | 10001 |
| 104 | New York | New York | 2,015,087 | New York Life Insurance | 10010 |
| 105 | New York | New York | 2,015,087 | TIAA | 10017 |
| 106 | New York | New York | 2,015,087 | Travelers | 10017 |
| 107 | New York | New York | 2,015,087 | Marsh & McLennan | 10036 |
| 108 | New York | New York | 2,015,087 | Apollo Global Management | 10019 |
| 109 | New York | New York | 2,015,087 | American International | 10020 |
| 110 | New York | New York | 2,015,087 | Bank of New York | 10286 |
| 111 | New York | New York | 2,015,087 | Warner Bros. Discovery | 10003 |
| 112 | New York | New York | 2,015,087 | KKR | 10001 |
| 113 | Pennsylvania | Erie | 1,970,149 | Erie Insurance | 16530 |
| 114 | Wisconsin | Madison | 1,918,919 | American Family Insurance | 53783 |
| 115 | California | Newport Beach | 1,880,504 | Pacific Life | 92660 |
| 116 | California | Newport Beach | 1,880,504 | Chipotle Mexican Grill | 92660 |
| 117 | Pennsylvania | Radnor | 1,877,551 | Lincoln National | 19087 |
| 118 | California | Irvine | 1,839,080 | Ingram Micro | 92612 |
| 119 | Illinois | Bloomington | 1,824,926 | State Farm | 61710 |
| 120 | Minnesota | Arden Hills | 1,800,000 | Land O'Lakes | 55126 |
| 121 | Colorado | Denver | 1,799,566 | VF | 80202 |
| 122 | Colorado | Denver | 1,799,566 | Ovintiv | 80202 |
| 123 | Colorado | Denver | 1,799,566 | Newmont | 80237 |
| 124 | Colorado | Denver | 1,799,566 | DaVita | 80202 |
| 125 | Arizona | Scottsdale | 1,797,917 | Reliance | 85254 |
| 126 | Arizona | Scottsdale | 1,797,917 | Taylor Morrison Home | 85251 |
| 127 | Rhode Island | Johnston | 1,793,103 | FM | 02919 |
| 128 | Maryland | Baltimore | 1,661,972 | Constellation Energy | 21231 |
| 129 | California | Foster City | 1,636,364 | Gilead Sciences | 94404 |
| 130 | Texas | Irving | 1,585,504 | Commercial Metals | 75039 |
| 131 | Texas | Irving | 1,585,504 | Vistra | 75039 |
| 132 | Texas | Irving | 1,585,504 | McKesson | 75039 |
| 133 | Texas | Irving | 1,585,504 | Builders FirstSource | 75039 |
| 134 | Texas | Irving | 1,585,504 | Kimberly-Clark | 75038 |
| 135 | Texas | Irving | 1,585,504 | Celanese | 75039 |
| 136 | Texas | Irving | 1,585,504 | Fluor | 75039 |
| 137 | Texas | Irving | 1,585,504 | Caterpillar | 75039 |
| 138 | California | Woodland Hills | 1,565,657 | Farmers Insurance Exchange | 91367 |
| 139 | California | Fremont | 1,561,882 | TD Synnex | 94538 |
| 140 | California | Fremont | 1,561,882 | Lam Research | 94538 |
| 141 | Wisconsin | Milwaukee | 1,558,929 | Rockwell Automation | 53204 |
| 142 | Wisconsin | Milwaukee | 1,558,929 | WEC Energy | 53203 |
| 143 | Wisconsin | Milwaukee | 1,558,929 | Manpower | 53212 |
| 144 | Wisconsin | Milwaukee | 1,558,929 | Fiserv | 53203 |
| 145 | Wisconsin | Milwaukee | 1,558,929 | Northwestern Mutual | 53202 |
| 146 | Arkansas | El Dorado | 1,543,103 | Murphy USA | 71730 |
| 147 | Virginia | Richmond | 1,492,470 | ARKO | 23227 |
| 148 | Virginia | Richmond | 1,492,470 | Dominion Energy | 23219 |
| 149 | Virginia | Richmond | 1,492,470 | Altria | 23230 |
| 150 | Virginia | Richmond | 1,492,470 | CarMax | 23238 |
| 151 | Virginia | Richmond | 1,492,470 | Performance Food | 23238 |
| 152 | Texas | Dallas | 1,489,891 | Texas Instruments | 75243 |
| 153 | Texas | Dallas | 1,489,891 | AECOM | 75240 |
| 154 | Texas | Dallas | 1,489,891 | Tenet Healthcare | 75254 |
| 155 | Texas | Dallas | 1,489,891 | AT&T | 75202 |
| 156 | Texas | Dallas | 1,489,891 | Energy Transfer | 75225 |
| 157 | Texas | Dallas | 1,489,891 | CBRE | 75201 |
| 158 | Texas | Dallas | 1,489,891 | HF Sinclair | 75219 |
| 159 | Texas | Dallas | 1,489,891 | Southwest Airlines | 75235 |
| 160 | Texas | Dallas | 1,489,891 | Jacobs Solutions | 75201 |
| 161 | Georgia | Columbus | 1,488,189 | Aflac | 31999 |
| 162 | California | Oakland | 1,486,595 | PG&E | 94612 |
| 163 | California | Oakland | 1,486,595 | Block | 94612 |
| 164 | Florida | Juno Beach | 1,476,190 | NextEra Energy | 33408 |
| 165 | Ohio | Columbus | 1,472,016 | Nationwide | 43215 |
| 166 | Ohio | Columbus | 1,472,016 | American Electric Power | 43215 |
| 167 | Ohio | Columbus | 1,472,016 | Huntington Bancshares | 43287 |
| 168 | Rhode Island | Woonsocket | 1,436,609 | CVS Health | 02895 |
| 169 | New Jersey | Princeton | 1,416,422 | Bristol-Myers Squibb | 08543 |
| 170 | Illinois | Vernon Hills | 1,390,728 | CDW | 60061 |
| 171 | Connecticut | Hartford | 1,387,435 | Hartford Insurance | 06155 |
| 172 | Massachusetts | Boston | 1,361,465 | State Street | 02114 |
| 173 | Massachusetts | Boston | 1,361,465 | Vertex Pharmaceuticals | 02210 |
| 174 | Massachusetts | Boston | 1,361,465 | American Tower | 02116 |
| 175 | Massachusetts | Boston | 1,361,465 | Wayfair | 02116 |
| 176 | Massachusetts | Boston | 1,361,465 | Liberty Mutual Insurance | 02116 |
| 177 | Ohio | Cincinnati | 1,354,012 | Fifth Third Bancorp | 45263 |
| 178 | Ohio | Cincinnati | 1,354,012 | Kroger | 45202 |
| 179 | Ohio | Cincinnati | 1,354,012 | Procter & Gamble | 45202 |
| 180 | Ohio | Cincinnati | 1,354,012 | Western & Southern Financial | 45202 |
| 181 | Ohio | Cincinnati | 1,354,012 | Cintas | 45262 |
| 182 | Ohio | Cincinnati | 1,354,012 | American Financial | 45202 |
| 183 | Indiana | Fort Wayne | 1,346,154 | Steel Dynamics | 46804 |
| 184 | Michigan | Detroit | 1,335,097 | Ally Financial | 48226 |
| 185 | Michigan | Detroit | 1,335,097 | DTE Energy | 48226 |
| 186 | Michigan | Detroit | 1,335,097 | General Motors | 48265 |
| 187 | New Jersey | Newark | 1,324,914 | Prudential Financial | 07102 |
| 188 | New Jersey | Newark | 1,324,914 | Public Service Enterprise | 07102 |
| 189 | Colorado | Centennial | 1,297,674 | Arrow Electronics | 80112 |
| 190 | California | Mountain View | 1,291,496 | Alphabet | 94043 |
| 191 | California | Mountain View | 1,291,496 | Intuit | 94043 |
| 192 | Illinois | Rosemont | 1,263,333 | US Foods | 60018 |
| 193 | California | Rosemead | 1,257,143 | Edison International | 91770 |
| 194 | Connecticut | Greenwich | 1,252,711 | W.R. Berkley | 06830 |
| 195 | Connecticut | Greenwich | 1,252,711 | GXO Logistics | 06831 |
| 196 | Connecticut | Greenwich | 1,252,711 | XPO | 06831 |
| 197 | Connecticut | Greenwich | 1,252,711 | Interactive Brokers | 06830 |
| 198 | California | Corona | 1,250,000 | Monster Beverage | 92879 |
| 199 | Missouri | St. Louis | 1,216,159 | Emerson Electric | 63136 |
| 200 | Missouri | St. Louis | 1,216,159 | Post s | 63144 |
| 201 | Missouri | St. Louis | 1,216,159 | Core & Main | 63146 |
| 202 | Missouri | St. Louis | 1,216,159 | Graybar Electric | 63105 |
| 203 | Missouri | St. Louis | 1,216,159 | Centene | 63105 |
| 204 | Oregon | Medford | 1,211,921 | Lithia Motors | 97501 |
| 205 | Virginia | Herndon | 1,209,877 | QXO Building Products | 20170 |
| 206 | Michigan | Midland | 1,194,444 | Dow | 48674 |
| 207 | California | Thousand Oaks | 1,192,857 | Amgen | 91320 |
| 208 | Tennessee | Chattanooga | 1,183,486 | Unum | 37402 |
| 209 | California | Palo Alto | 1,170,177 | Broadcom | 94304 |
| 210 | California | Palo Alto | 1,170,177 | HP | 94304 |
| 211 | Illinois | Northbrook | 1,161,232 | Allstate | 60062 |
| 212 | Indiana | Indianapolis | 1,144,158 | Corteva | 46268 |
| 213 | Indiana | Indianapolis | 1,144,158 | Elevance Health | 46204 |
| 214 | Indiana | Indianapolis | 1,144,158 | Eli Lilly | 46285 |
| 215 | Minnesota | Eden Prairie | 1,141,679 | UnitedHealth | 55344 |
| 216 | Minnesota | Eden Prairie | 1,141,679 | C.H. Robinson Worldwide | 55347 |
| 217 | Ohio | Mayfield Village | 1,137,255 | Progressive | 44143 |
| 218 | Illinois | Riverwoods | 1,123,810 | Discover Financial | 60015 |
| 219 | California | Santa Clara | 1,122,844 | Applied Materials | 95054 |
| 220 | California | Santa Clara | 1,122,844 | Palo Alto Networks | 95054 |
| 221 | California | Santa Clara | 1,122,844 | Advanced Micro Devices | 95054 |
| 222 | California | Santa Clara | 1,122,844 | Nvidia | 95051 |
| 223 | California | Santa Clara | 1,122,844 | ServiceNow | 95054 |
| 224 | California | Santa Clara | 1,122,844 | Intel | 95054 |
| 225 | Nebraska | Omaha | 1,116,963 | Union Pacific | 68179 |
| 226 | Nebraska | Omaha | 1,116,963 | Peter Kiewit Sons' | 68102 |
| 227 | Nebraska | Omaha | 1,116,963 | Mutual of Omaha Insurance | 68175 |
| 228 | Nebraska | Omaha | 1,116,963 | Berkshire Hathaway | 68131 |
| 229 | Minnesota | Minneapolis | 1,108,596 | General Mills | 55426 |
| 230 | Minnesota | Minneapolis | 1,108,596 | U.S. Bancorp | 55402 |
| 231 | Minnesota | Minneapolis | 1,108,596 | Xcel Energy | 55401 |
| 232 | Minnesota | Minneapolis | 1,108,596 | Target | 55403 |
| 233 | Minnesota | Minneapolis | 1,108,596 | Thrivent Financial for Lutherans | 55415 |
| 234 | Minnesota | Minneapolis | 1,108,596 | Ameriprise Financial | 55474 |
| 235 | Michigan | Dearborn | 1,081,871 | Ford Motor | 48126 |
| 236 | New York | Victor | 1,075,269 | Constellation Brands | 14564 |
| 237 | Washington | Redmond | 1,075,000 | Microsoft | 98052 |
| 238 | Florida | Fort Lauderdale | 1,067,729 | AutoNation | 33301 |
| 239 | Michigan | Bloomfield Hills | 1,055,363 | Penske Automotive | 48302 |
| 240 | Illinois | North Chicago | 1,023,636 | AbbVie | 60064 |
| 241 | California | San Francisco | 1,023,212 | Wells Fargo | 94104 |
| 242 | California | San Francisco | 1,023,212 | Uber | 94158 |
| 243 | California | San Francisco | 1,023,212 | Salesforce | 94105 |
| 244 | California | San Francisco | 1,023,212 | Visa | 94105 |
| 245 | California | San Francisco | 1,023,212 | Williams-Sonoma | 94109 |
| 246 | California | San Francisco | 1,023,212 | Prologis | 94111 |
| 247 | California | San Francisco | 1,023,212 | Gap | 94105 |
| 248 | California | San Francisco | 1,023,212 | DoorDash | 94107 |
| 249 | California | San Francisco | 1,023,212 | Airbnb | 94103 |
| 250 | Texas | New Braunfels | 987,342 | Rush Enterprises | 78130 |
| 251 | California | San Diego | 986,470 | Sempra | 92101 |
| 252 | California | San Diego | 986,470 | Qualcomm | 92121 |
| 253 | California | San Diego | 986,470 | LPL Financial s | 92121 |
| 254 | Louisiana | New Orleans | 967,480 | Entergy | 70113 |
| 255 | California | San Jose | 943,023 | Adobe | 95110 |
| 256 | California | San Jose | 943,023 | PayPal | 95131 |
| 257 | California | San Jose | 943,023 | Cisco Systems | 95134 |
| 258 | California | San Jose | 943,023 | Ebay | 95125 |
| 259 | California | San Jose | 943,023 | Sanmina | 95134 |
| 260 | California | San Jose | 943,023 | Western Digital | 95119 |
| 261 | California | San Jose | 943,023 | Super Micro Computer | 95131 |
| 262 | New York | Tarrytown | 940,397 | Regeneron Pharmaceuticals | 10591 |
| 263 | Illinois | Moline | 931,532 | Deere | 61265 |
| 264 | Ohio | Orrville | 911,111 | J.M. Smucker | 44667 |
| 265 | Pennsylvania | Allentown | 904,418 | PPL | 18101 |
| 266 | Pennsylvania | Allentown | 904,418 | Air Products & Chemicals | 18106 |
| 267 | Michigan | Jackson | 903,614 | CMS Energy | 49201 |
| 268 | North Carolina | Charlotte | 891,162 | Truist Financial | 28202 |
| 269 | North Carolina | Charlotte | 891,162 | Duke Energy | 28202 |
| 270 | North Carolina | Charlotte | 891,162 | Bank of America | 28255 |
| 271 | North Carolina | Charlotte | 891,162 | Honeywell | 28202 |
| 272 | North Carolina | Charlotte | 891,162 | Nucor | 28211 |
| 273 | North Carolina | Charlotte | 891,162 | Sonic Automotive | 28211 |
| 274 | Texas | Round Rock | 885,185 | Dell Technologies | 78682 |
| 275 | New Jersey | Rahway | 867,568 | Merck | 07065 |
| 276 | Massachusetts | Cambridge | 865,371 | Biogen | 02142 |
| 277 | Massachusetts | Cambridge | 865,371 | GE Vernova | 02141 |
| 278 | California | Beverly Hills | 854,339 | Endeavor | 90210 |
| 279 | California | Beverly Hills | 854,339 | Live Nation Entertainment | 90210 |
| 280 | Washington | Bellevue | 840,224 | Paccar | 98004 |
| 281 | Washington | Bellevue | 840,224 | Expeditors International of Washington | 98006 |
| 282 | Colorado | Englewood | 839,800 | EchoStar | 80112 |
| 283 | Colorado | Englewood | 839,800 | QVC | 80112 |
| 284 | California | San Mateo | 833,333 | Franklin Resources | 94403 |
| 285 | Iowa | Des Moines | 817,259 | Principal Financial | 50392 |
| 286 | Georgia | Duluth | 817,083 | AGCO | 30096 |
| 287 | Georgia | Duluth | 817,083 | Asbury Automotive | 30097 |
| 288 | Florida | Jacksonville | 813,394 | GuideWell Mutual | 32246 |
| 289 | Florida | Jacksonville | 813,394 | Fidelity National Information | 32202 |
| 290 | Florida | Jacksonville | 813,394 | Fidelity National Financial | 32204 |
| 291 | Florida | Jacksonville | 813,394 | CSX | 32202 |
| 292 | Texas | Westlake | 809,969 | Charles Schwab | 76262 |
| 293 | Arizona | Tempe | 787,356 | Carvana | 85281 |
| 294 | Kentucky | Louisville | 778,332 | Humana | 40202 |
| 295 | Kentucky | Louisville | 778,332 | BrightSpring Health Services | 40222 |
| 296 | Kentucky | Louisville | 778,332 | Yum Brands | 40213 |
| 297 | Washington | Issaquah | 764,264 | Costco | 98027 |
| 298 | Illinois | Oak Brook | 760,000 | Ace Hardware | 60523 |
| 299 | Arizona | Phoenix | 757,793 | Avnet | 85034 |
| 300 | Arizona | Phoenix | 757,793 | Sprouts Farmers Market | 85054 |
| 301 | Arizona | Phoenix | 757,793 | Republic Services | 85054 |
| 302 | Arizona | Phoenix | 757,793 | Freeport-McMoRan | 85004 |
| 303 | Colorado | Westminster | 756,250 | Ball | 80021 |
| 304 | Rhode Island | Providence | 738,370 | Citizens Financial | 02903 |
| 305 | Rhode Island | Providence | 738,370 | Textron | 02903 |
| 306 | Rhode Island | Providence | 738,370 | United Natural Foods | 02908 |
| 307 | Minnesota | St. Paul | 730,456 | Securian Financial | 55101 |
| 308 | Minnesota | St. Paul | 730,456 | Ecolab | 55102 |
| 309 | Minnesota | St. Paul | 730,456 | 3M | 55144 |
| 310 | Ohio | Evendale | 730,189 | General Electric | 45215 |
| 311 | Virginia | Arlington | 724,049 | AES | 22203 |
| 312 | Virginia | Arlington | 724,049 | RTX | 22209 |
| 313 | Virginia | Arlington | 724,049 | Boeing | 22202 |
| 314 | Georgia | Atlanta | 711,349 | Genuine Parts | 30339 |
| 315 | Georgia | Atlanta | 711,349 | Southern | 30308 |
| 316 | Georgia | Atlanta | 711,349 | Home Depot | 30339 |
| 317 | Georgia | Atlanta | 711,349 | Coca-Cola | 30313 |
| 318 | Georgia | Atlanta | 711,349 | Pulte | 30326 |
| 319 | Georgia | Atlanta | 711,349 | Norfolk Southern | 30308 |
| 320 | Georgia | Atlanta | 711,349 | Delta Airlines | 30354 |
| 321 | Georgia | Atlanta | 711,349 | Assurant | 30339 |
| 322 | Georgia | Atlanta | 711,349 | Intercontinental Exchange | 30328 |
| 323 | Georgia | Atlanta | 711,349 | Global Payments | 30326 |
| 324 | Georgia | Atlanta | 711,349 | Graphic Packaging | 30328 |
| 325 | Georgia | Atlanta | 711,349 | Newell Brands | 30328 |
| 326 | Georgia | Atlanta | 711,349 | UPS | 30328 |
| 327 | New Jersey | Summit | 704,545 | Kenvue | 07901 |
| 328 | Connecticut | Stamford | 699,383 | Philip Morris | 06901 |
| 329 | Connecticut | Stamford | 699,383 | Charter Communications | 06902 |
| 330 | Connecticut | Stamford | 699,383 | United Rentals | 06902 |
| 331 | Connecticut | Stamford | 699,383 | Synchrony Financial | 06902 |
| 332 | Illinois | Chicago | 677,019 | United Airlines | 60606 |
| 333 | Illinois | Chicago | 677,019 | Kraft Heinz | 60601 |
| 334 | Illinois | Chicago | 677,019 | Jones Lang LaSalle | 60601 |
| 335 | Illinois | Chicago | 677,019 | Archer Daniels Midland | 60601 |
| 336 | Illinois | Chicago | 677,019 | Conagra Brands | 60654 |
| 337 | Illinois | Chicago | 677,019 | Old Republic International | 60601 |
| 338 | Illinois | Chicago | 677,019 | Motorola Solutions | 60661 |
| 339 | Illinois | Chicago | 677,019 | McDonald's | 60607 |
| 340 | Illinois | Chicago | 677,019 | Molson Coors Beverage | 60606 |
| 341 | Illinois | Chicago | 677,019 | Mondelez | 60607 |
| 342 | Illinois | Chicago | 677,019 | Exelon | 60603 |
| 343 | Illinois | Chicago | 677,019 | GE HealthCare Technologies | 60661 |
| 344 | Illinois | Chicago | 677,019 | Northern Trust | 60603 |
| 345 | Illinois | Chicago | 677,019 | Kellanova | 60654 |
| 346 | Tennessee | Kingsport | 671,429 | Eastman Chemical | 37660 |
| 347 | Connecticut | Norwalk | 670,362 | EMCOR | 06851 |
| 348 | Connecticut | Norwalk | 670,362 | Booking s | 06854 |
| 349 | Ohio | Akron | 667,426 | Goodyear Tire & Rubber | 44316 |
| 350 | Ohio | Akron | 667,426 | FirstEnergy | 44308 |
| 351 | New Jersey | Camden | 666,667 | Campbell's | 08103 |
| 352 | Florida | Sunny Isles Beach | 666,667 | Icahn Enterprises | 33160 |
| 353 | Florida | Plantation | 661,111 | Chewy | 33322 |
| 354 | Illinois | Westchester | 660,714 | Ingredion | 60154 |
| 355 | Florida | Tampa | 658,696 | Crown s | 33637 |
| 356 | Florida | Tampa | 658,696 | Mosaic | 33602 |
| 357 | Kansas | Merriam | 650,000 | Seaboard | 66202 |
| 358 | California | Milpitas | 649,007 | KLA | 95035 |
| 359 | New York | Long Island City | 647,693 | Altice USA | 11101 |
| 360 | New York | Long Island City | 647,693 | JetBlue Airways | 11101 |
| 361 | Oregon | Beaverton | 647,355 | Nike | 97005 |
| 362 | New Jersey | New Brunswick | 643,012 | Johnson & Johnson | 08933 |
| 363 | Michigan | Byron Center | 633,333 | SpartanNash | 49315 |
| 364 | Pennsylvania | Pittsburgh | 618,757 | WESCO International | 15219 |
| 365 | Pennsylvania | Pittsburgh | 618,757 | Westinghouse Air Brake Technologies | 15212 |
| 366 | Pennsylvania | Pittsburgh | 618,757 | Alcoa | 15212 |
| 367 | Pennsylvania | Pittsburgh | 618,757 | United States Steel | 15219 |
| 368 | Pennsylvania | Pittsburgh | 618,757 | PPG Industries | 15272 |
| 369 | Pennsylvania | Pittsburgh | 618,757 | Howmet Aerospace | 15212 |
| 370 | Pennsylvania | Pittsburgh | 618,757 | PNC | 15222 |
| 371 | Illinois | Lake Forest | 616,727 | Packaging Corp. of America | 60045 |
| 372 | Illinois | Lake Forest | 616,727 | W.W. Grainger | 60045 |
| 373 | New York | Buffalo | 610,860 | M&T Bank | 14203 |
| 374 | Virginia | Glen Allen | 607,876 | Owens & Minor | 23060 |
| 375 | Virginia | Glen Allen | 607,876 | Markel | 23060 |
| 376 | California | Redwood City | 597,225 | Electronic Arts | 94065 |
| 377 | California | Redwood City | 597,225 | Equinix | 94065 |
| 378 | California | Manhattan Beach | 596,026 | Skechers U.S.A. | 90266 |
| 379 | Minnesota | Austin | 595,000 | Hormel Foods | 55912 |
| 380 | Virginia | Reston | 583,503 | Science Applications International | 20190 |
| 381 | Virginia | Reston | 583,503 | CACI International | 20190 |
| 382 | Virginia | Reston | 583,503 | NVR | 20190 |
| 383 | Virginia | Reston | 583,503 | Leidos s | 20190 |
| 384 | Virginia | Reston | 583,503 | General Dynamics | 20190 |
| 385 | Pennsylvania | Hershey | 580,311 | Hershey | 17033 |
| 386 | Wisconsin | Oshkosh | 578,378 | Oshkosh | 54902 |
| 387 | Texas | Austin | 555,290 | Tesla | 78725 |
| 388 | Texas | Austin | 555,290 | Oracle | 78741 |
| 389 | Virginia | Newport News | 553,539 | Ferguson | 23606 |
| 390 | Virginia | Newport News | 553,539 | Huntington Ingalls Industries | 23607 |
| 391 | Alabama | Birmingham | 548,129 | Regions Financial | 35203 |
| 392 | Alabama | Birmingham | 548,129 | Vulcan Materials | 35242 |
| 393 | North Carolina | Raleigh | 547,068 | Advance Auto Parts | 27609 |
| 394 | North Carolina | Raleigh | 547,068 | First Citizens BancShares | 27609 |
| 395 | New York | Purchase | 543,477 | Mastercard | 10577 |
| 396 | New York | Purchase | 543,477 | PepsiCo | 10577 |
| 397 | California | Sunnyvale | 538,462 | Intuitive Surgical | 94086 |
| 398 | Louisiana | Monroe | 524,000 | Lumen Technologies | 71203 |
| 399 | Massachusetts | Burlington | 523,810 | Keurig Dr Pepper | 01803 |
| 400 | Florida | Palm Beach Gardens | 516,667 | Carrier Global | 33418 |
| 401 | Delaware | Wilmington | 516,667 | DuPont | 19805 |
| 402 | New York | Melville | 508,000 | Henry Schein | 11747 |
| 403 | Florida | St. Petersburg | 496,815 | Jabil | 33716 |
| 404 | Florida | St. Petersburg | 496,815 | Raymond James Financial | 33716 |
| 405 | Illinois | Deerfield | 491,159 | Baxter International | 60015 |
| 406 | Illinois | Deerfield | 491,159 | Walgreens | 60015 |
| 407 | Indiana | Columbus | 489,943 | Cummins | 47201 |
| 408 | Minnesota | Richfield | 488,235 | Best Buy | 55423 |
| 409 | Arizona | Chandler | 474,599 | Insight Enterprises | 85286 |
| 410 | Arizona | Chandler | 474,599 | Microchip Technology | 85224 |
| 411 | Ohio | Cleveland | 470,144 | TransDigm | 44115 |
| 412 | Ohio | Cleveland | 470,144 | KeyCorp | 44114 |
| 413 | Ohio | Cleveland | 470,144 | Cleveland-Cliffs | 44114 |
| 414 | Ohio | Cleveland | 470,144 | Parker-Hannifin | 44124 |
| 415 | Ohio | Cleveland | 470,144 | Sherwin-Williams | 44115 |
| 416 | Massachusetts | Marlborough | 468,153 | BJ's Wholesale Club | 01752 |
| 417 | Massachusetts | Marlborough | 468,153 | Boston Scientific | 01752 |
| 418 | Idaho | Boise | 462,883 | Micron Technology | 83716 |
| 419 | Idaho | Boise | 462,883 | Albertsons | 83706 |
| 420 | Pennsylvania | Canonsburg | 459,375 | Viatris | 15317 |
| 421 | Florida | Melbourne | 453,191 | L3Harris Technologies | 32919 |
| 422 | Indiana | Warsaw | 452,941 | Zimmer Biomet s | 46580 |
| 423 | Iowa | Ankeny | 450,151 | Casey's General Stores | 50021 |
| 424 | Indiana | Elkhart | 448,430 | THOR Industries | 46514 |
| 425 | California | Burbank | 445,854 | Walt Disney | 91521 |
| 426 | Michigan | Livonia | 433,333 | Masco | 48152 |
| 427 | Michigan | Portage | 426,415 | Stryker | 49002 |
| 428 | Virginia | Falls Church | 422,680 | Northrop Grumman | 22042 |
| 429 | California | Pleasanton | 409,756 | Workday | 94588 |
| 430 | Texas | Fort Worth | 406,602 | American Airlines | 76155 |
| 431 | Washington | Seattle | 398,315 | Expedia | 98119 |
| 432 | Washington | Seattle | 398,315 | Nordstrom | 98101 |
| 433 | Washington | Seattle | 398,315 | Coupang | 98101 |
| 434 | Washington | Seattle | 398,315 | Starbucks | 98134 |
| 435 | Washington | Seattle | 398,315 | Amazon | 98109 |
| 436 | Washington | Seattle | 398,315 | Alaska Air | 98188 |
| 437 | Massachusetts | Wilmington | 391,667 | Analog Devices | 01887 |
| 438 | North Carolina | Mooresville | 388,399 | Lowe's | 28117 |
| 439 | Arkansas | Springdale | 386,232 | Tyson Foods | 72762 |
| 440 | Minnesota | Maplewood | 377,273 | Solventum | 55144 |
| 441 | Michigan | Benton Harbor | 377,273 | Whirlpool | 49022 |
| 442 | Maryland | Bethesda | 374,356 | Marriott International | 20814 |
| 443 | Maryland | Bethesda | 374,356 | Lockheed Martin | 20817 |
| 444 | Pennsylvania | Philadelphia | 372,456 | Comcast | 19103 |
| 445 | Pennsylvania | Philadelphia | 372,456 | Aramark | 19103 |
| 446 | Illinois | Abbott Park | 368,421 | Abbott Laboratories | 60064 |
| 447 | Illinois | Glenview | 361,364 | Illinois Tool Works | 60025 |
| 448 | Arkansas | Lowell | 360,119 | J.B. Hunt Transport Services | 72745 |
| 449 | Pennsylvania | Coraopolis | 358,289 | Dick's Sporting Goods | 15108 |
| 450 | Minnesota | Winona | 357,143 | Fastenal | 55987 |
| 451 | Illinois | Downers Grove | 350,000 | Dover | 60515 |
| 452 | Florida | Estero | 346,154 | Hertz | 33928 |
| 453 | Arkansas | Bentonville | 324,286 | Walmart | 72712 |
| 454 | Connecticut | New Britain | 317,526 | Stanley Black & Decker | 06053 |
| 455 | Florida | Coral Gables | 316,448 | Ryder System | 33134 |
| 456 | Florida | Coral Gables | 316,448 | MasTec | 33134 |
| 457 | Tennessee | Antioch | 306,383 | LKQ | 37013 |
| 458 | New Jersey | Roseland | 300,000 | Automatic Data Processing | 07068 |
| 459 | Tennessee | Memphis | 298,002 | International Paper | 38197 |
| 460 | Tennessee | Memphis | 298,002 | AutoZone | 38103 |
| 461 | Tennessee | Memphis | 298,002 | FedEx | 38120 |
| 462 | Missouri | Des Peres | 296,364 | Edward Jones | 63131 |
| 463 | Indiana | Evansville | 292,857 | Berry Global | 47710 |
| 464 | Illinois | Bolingbrook | 289,744 | Ulta Beauty | 60440 |
| 465 | New Jersey | Franklin Lakes | 272,973 | Becton Dickinson | 07417 |
| 466 | Washington | Sumner | 271,795 | Lululemon athletica | 98390 |
| 467 | Wisconsin | Menomonee Falls | 270,000 | Kohl's | 53051 |
| 468 | Michigan | Auburn Hills | 267,540 | Autoliv | 48326 |
| 469 | Michigan | Auburn Hills | 267,540 | BorgWarner | 48326 |
| 470 | Nevada | Las Vegas | 265,535 | Las Vegas Sands | 89113 |
| 471 | Nevada | Las Vegas | 265,535 | MGM Resorts International | 89109 |
| 472 | Tennessee | Nashville | 260,517 | HCA Healthcare | 37203 |
| 473 | Ohio | Westerville | 258,065 | Vertiv s | 43082 |
| 474 | Georgia | Calhoun | 257,757 | Mohawk Industries | 30701 |
| 475 | Ohio | Mentor | 251,429 | Avery Dennison | 44060 |
| 476 | Tennessee | Franklin | 240,000 | Community Health Systems | 37067 |
| 477 | Florida | Lakeland | 236,078 | Publix Super Markets | 33811 |
| 478 | New York | Corning | 232,682 | Corning | 14831 |
| 479 | Nevada | Reno | 226,000 | Caesars Entertainment | 89501 |
| 480 | New Jersey | Burlington | 224,101 | Burlington Stores | 08016 |
| 481 | New York | Armonk | 220,738 | IBM | 10504 |
| 482 | Virginia | Chesapeake | 220,630 | Dollar Tree | 23320 |
| 483 | Tennessee | Goodlettsville | 209,063 | Dollar General | 37072 |
| 484 | Illinois | Rolling Meadows | 207,143 | Arthur J. Gallagher | 60008 |
| 485 | North Carolina | Burlington | 198,777 | Labcorp s | 27215 |
| 486 | Connecticut | Farmington | 198,611 | Otis Worldwide | 06032 |
| 487 | California | Dublin | 197,196 | Ross Stores | 94568 |
| 488 | New Jersey | Secaucus | 196,040 | Quest Diagnostics | 07094 |
| 489 | Missouri | Springfield | 195,093 | O'Reilly Automotive | 65802 |
| 490 | Pennsylvania | King of Prussia | 180,571 | Universal Health Services | 19406 |
| 491 | North Carolina | Durham | 175,000 | IQVIA s | 27703 |
| 492 | Massachusetts | Framingham | 154,945 | TJX | 01701 |
| 493 | Michigan | Southfield | 134,139 | Lear | 48033 |
| 494 | Connecticut | Wallingford | 121,600 | Amphenol | 06492 |
| 495 | Virginia | Ashburn | 105,385 | DXC Technology | 20147 |
| 496 | Florida | Orlando | 59,655 | Darden Restaurants | 32837 |
| 497 | New Jersey | Teaneck | 58,492 | Cognizant Technology | 07666 |
| 498 | Texas | Plano | 46,029 | Yum China s | 75074 |
| 499 | California | Newark | 21,333 | Concentrix | 94560 |
In [199]:
gdfusactavreff = gdfusact.merge(dfctavreff, how = 'inner', on = ['Zip Code'])
gdfusactavreff = gdfusactavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [200]:
mctavreff = gdfusactavreff.explore(column='Efficiency', name='The Average Efficiency in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctavreff)
mctavreff
Out[200]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
Statistics in Industry Level¶
In [59]:
# Grab all distinct Industry names
dfins = df[['Industry']]
dfins = dfins.drop_duplicates()
dfins = dfins.reset_index(drop=True)
inslist = dfins.to_numpy().tolist()
inslist[1][0]
for ins in inslist:
print(ins[0])
print("---------------")
General Merchandisers --------------- Internet Services and Retailing --------------- Health Care: Insurance and Managed Care --------------- Computers, Office Equipment --------------- Health Care: Pharmacy and Other Services --------------- Insurance: Property and Casualty (Stock) --------------- Petroleum Refining --------------- Wholesalers: Health Care --------------- Commercial Banks --------------- Computer Software --------------- Motor Vehicles & Parts --------------- Specialty Retailers: Other --------------- Diversified Financials --------------- Food & Drug Stores --------------- Telecommunications --------------- Semiconductors and Other Electronic Components --------------- Insurance: Property and Casualty (Mutual) --------------- Food Consumer Products --------------- Entertainment --------------- Mail, Package and Freight Delivery --------------- Pharmaceuticals --------------- Food Production --------------- Household and Personal Products --------------- Pipelines --------------- Aerospace & Defense --------------- Wholesalers: Food and Grocery --------------- Insurance: Life, Health (Stock) --------------- Health Care: Medical Facilities --------------- Construction and Farm Machinery --------------- Information Technology Services --------------- Insurance: Life, Health (Mutual) --------------- Airlines --------------- Wholesalers: Electronics and Office Equipment --------------- Mining, Crude-Oil Production --------------- Specialty Retailers: Apparel --------------- Network and Other Communications Equipment --------------- Apparel --------------- Beverages --------------- Chemicals --------------- Scientific, Photographic and Control Equipment --------------- Energy --------------- Medical Products and Equipment --------------- Industrial Machinery --------------- Tobacco --------------- Homebuilders --------------- Automotive Retailing, Services --------------- Food Services --------------- Financial Data Services --------------- Real Estate --------------- Metals --------------- Utilities: Gas and Electric --------------- Securities --------------- Wholesalers: Diversified --------------- Oil and Gas Equipment, Services --------------- Hotels, Casinos, Resorts --------------- Railroads --------------- Engineering & Construction --------------- Waste Management --------------- Diversified Outsourcing Services --------------- Packaging, Containers --------------- Transportation and Logistics --------------- Electronics, Electrical Equip. --------------- Building Materials, Glass --------------- Advertising, Marketing --------------- Trucking, Truck Leasing --------------- Home Equipment, Furnishings --------------- Publishing, Printing ---------------
In [ ]:
In [61]:
# Check the Largest Revenue Company in each Industry
dfinsmaxrevco = df.head(1)
for ins in inslist[0:]:
dfin = df.where(df['Industry'] == ins[0]).dropna()
mninmaxrev = dfin['Revenue (rounded)'].max()
dfinmaxrevco = dfin.where(dfin['Revenue (rounded)'] == mninmaxrev).dropna()
dfinsmaxrevco = pd.concat([dfinsmaxrevco, dfinmaxrevco], ignore_index=True)
dfinsmaxrevco = dfinsmaxrevco.drop(0)
dfinsmaxrevco[['Industry','State','City','Company','Zip Code','Revenue (rounded)']].sort_values(by='Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[61]:
| Industry | State | City | Company | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | General Merchandisers | Arkansas | Bentonville | Walmart | 72712 | 681,000,000,000 |
| 1 | Internet Services and Retailing | Washington | Seattle | Amazon | 98109 | 638,000,000,000 |
| 2 | Health Care: Insurance and Managed Care | Minnesota | Eden Prairie | UnitedHealth | 55344 | 400,300,000,000 |
| 3 | Computers, Office Equipment | California | Cupertino | Apple | 95014 | 391,000,000,000 |
| 4 | Health Care: Pharmacy and Other Services | Rhode Island | Woonsocket | CVS Health | 02895 | 372,800,000,000 |
| 5 | Insurance: Property and Casualty (Stock) | Nebraska | Omaha | Berkshire Hathaway | 68131 | 371,400,000,000 |
| 6 | Petroleum Refining | Texas | Spring | Exxon Mobil | 77389 | 349,600,000,000 |
| 7 | Wholesalers: Health Care | Texas | Irving | McKesson | 75039 | 309,000,000,000 |
| 8 | Commercial Banks | New York | New York | JPMorgan Chase | 10017 | 278,900,000,000 |
| 9 | Computer Software | Washington | Redmond | Microsoft | 98052 | 245,100,000,000 |
| 10 | Motor Vehicles & Parts | Michigan | Detroit | General Motors | 48265 | 187,400,000,000 |
| 11 | Specialty Retailers: Other | Georgia | Atlanta | Home Depot | 30339 | 159,500,000,000 |
| 12 | Diversified Financials | District of Columbia | Washington | Fannie Mae | 20005 | 152,700,000,000 |
| 13 | Food & Drug Stores | Illinois | Deerfield | Walgreens | 60015 | 147,700,000,000 |
| 14 | Telecommunications | New York | New York | Verizon | 10036 | 134,800,000,000 |
| 15 | Semiconductors and Other Electronic Components | California | Santa Clara | Nvidia | 95051 | 130,500,000,000 |
| 16 | Insurance: Property and Casualty (Mutual) | Illinois | Bloomington | State Farm | 61710 | 123,000,000,000 |
| 17 | Food Consumer Products | New York | Purchase | PepsiCo | 10577 | 91,900,000,000 |
| 18 | Entertainment | California | Burbank | Walt Disney | 91521 | 91,400,000,000 |
| 19 | Mail, Package and Freight Delivery | Georgia | Atlanta | UPS | 30328 | 91,100,000,000 |
| 20 | Pharmaceuticals | New Jersey | New Brunswick | Johnson & Johnson | 08933 | 88,800,000,000 |
| 21 | Food Production | Illinois | Chicago | Archer Daniels Midland | 60601 | 85,500,000,000 |
| 22 | Household and Personal Products | Ohio | Cincinnati | Procter & Gamble | 45202 | 84,000,000,000 |
| 23 | Pipelines | Texas | Dallas | Energy Transfer | 75225 | 82,700,000,000 |
| 24 | Aerospace & Defense | Virginia | Arlington | RTX | 22209 | 80,700,000,000 |
| 25 | Wholesalers: Food and Grocery | Texas | Houston | Sysco | 77077 | 78,800,000,000 |
| 26 | Insurance: Life, Health (Stock) | New York | New York | MetLife | 10166 | 71,000,000,000 |
| 27 | Health Care: Medical Facilities | Tennessee | Nashville | HCA Healthcare | 37203 | 70,600,000,000 |
| 28 | Construction and Farm Machinery | Texas | Irving | Caterpillar | 75039 | 64,800,000,000 |
| 29 | Information Technology Services | New York | Armonk | IBM | 10504 | 62,800,000,000 |
| 30 | Insurance: Life, Health (Mutual) | New York | New York | New York Life Insurance | 10010 | 62,600,000,000 |
| 31 | Airlines | Georgia | Atlanta | Delta Airlines | 30354 | 61,600,000,000 |
| 32 | Wholesalers: Electronics and Office Equipment | California | Fremont | TD Synnex | 94538 | 58,500,000,000 |
| 33 | Mining, Crude-Oil Production | Texas | Houston | ConocoPhillips | 77079 | 57,000,000,000 |
| 34 | Specialty Retailers: Apparel | Massachusetts | Framingham | TJX | 01701 | 56,400,000,000 |
| 35 | Network and Other Communications Equipment | California | San Jose | Cisco Systems | 95134 | 53,800,000,000 |
| 36 | Apparel | Oregon | Beaverton | Nike | 97005 | 51,400,000,000 |
| 37 | Beverages | Georgia | Atlanta | Coca-Cola | 30313 | 47,100,000,000 |
| 38 | Chemicals | Michigan | Midland | Dow | 48674 | 43,000,000,000 |
| 39 | Scientific, Photographic and Control Equipment | Massachusetts | Waltham | Thermo Fisher Scientific | 02451 | 42,900,000,000 |
| 40 | Energy | Florida | Miami | World Kinect | 33178 | 42,200,000,000 |
| 41 | Medical Products and Equipment | Illinois | Abbott Park | Abbott Laboratories | 60064 | 42,000,000,000 |
| 42 | Industrial Machinery | North Carolina | Charlotte | Honeywell | 28202 | 38,500,000,000 |
| 43 | Tobacco | Connecticut | Stamford | Philip Morris | 06901 | 37,900,000,000 |
| 44 | Homebuilders | Texas | Arlington | D.R. Horton | 76011 | 36,800,000,000 |
| 45 | Automotive Retailing, Services | Oregon | Medford | Lithia Motors | 97501 | 36,600,000,000 |
| 46 | Food Services | Washington | Seattle | Starbucks | 98134 | 36,200,000,000 |
| 47 | Financial Data Services | California | San Francisco | Visa | 94105 | 35,900,000,000 |
| 48 | Real Estate | Texas | Dallas | CBRE | 75201 | 35,800,000,000 |
| 49 | Metals | North Carolina | Charlotte | Nucor | 28211 | 30,700,000,000 |
| 50 | Securities | New York | New York | KKR | 10001 | 29,900,000,000 |
| 51 | Utilities: Gas and Electric | North Carolina | Charlotte | Duke Energy | 28202 | 29,900,000,000 |
| 52 | Wholesalers: Diversified | Virginia | Newport News | Ferguson | 23606 | 29,600,000,000 |
| 53 | Oil and Gas Equipment, Services | Texas | Houston | Baker Hughes | 77079 | 27,800,000,000 |
| 54 | Hotels, Casinos, Resorts | Maryland | Bethesda | Marriott International | 20814 | 25,100,000,000 |
| 55 | Railroads | Nebraska | Omaha | Union Pacific | 68179 | 24,200,000,000 |
| 56 | Engineering & Construction | Texas | Houston | Quanta Services | 77008 | 23,700,000,000 |
| 57 | Waste Management | Texas | Houston | Waste Management | 77002 | 22,100,000,000 |
| 58 | Diversified Outsourcing Services | New Jersey | Roseland | Automatic Data Processing | 07068 | 19,200,000,000 |
| 59 | Packaging, Containers | Tennessee | Memphis | International Paper | 38197 | 18,600,000,000 |
| 60 | Transportation and Logistics | Minnesota | Eden Prairie | C.H. Robinson Worldwide | 55347 | 17,700,000,000 |
| 61 | Electronics, Electrical Equip. | Michigan | Benton Harbor | Whirlpool | 49022 | 16,600,000,000 |
| 62 | Building Materials, Glass | Texas | Irving | Builders FirstSource | 75039 | 16,400,000,000 |
| 63 | Advertising, Marketing | New York | New York | Omnicom | 10017 | 15,700,000,000 |
| 64 | Trucking, Truck Leasing | Arkansas | Lowell | J.B. Hunt Transport Services | 72745 | 12,100,000,000 |
| 65 | Home Equipment, Furnishings | Georgia | Calhoun | Mohawk Industries | 30701 | 10,800,000,000 |
| 66 | Publishing, Printing | New York | New York | News Corp. | 10036 | 10,100,000,000 |
In [62]:
# Join the Dataframe 'gdfusact' with 'dfinsmaxrevco' for the Largest Revenue Company in each Industry visualized by City
gdfusactinsmaxrevco = gdfusact.merge(dfinsmaxrevco, how = 'inner', on = ['Zip Code'])
gdfusactinsmaxrevco = gdfusactinsmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [63]:
# Join the Dataframe 'gdfsts' with 'dfinsmaxrevco' for the Largest Revenue Company in each Industry visualized by State
gdfstsinsmaxrevco = gdfsts.merge(dfinsmaxrevco, how = 'inner', on = ['State'])
gdfstsinsmaxrevco = gdfstsinsmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [64]:
# Draw multi-layer Map visualizing The Largest Revenue Company in each Industry by City and State
minsmaxrc = gdfstsinsmaxrevco.explore(column='Revenue (rounded)', name='The Largest Revenue Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxrevco.explore(m=minsmaxrc, column='Revenue (rounded)', name='The Largest Revenue Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxrc)
minsmaxrc
Out[64]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [66]:
# Check the Smallest Revenue Company in each Industry
dfinsminrevco = df.head(1)
for ins in inslist[0:]:
dfin = df.where(df['Industry'] == ins[0]).dropna()
mninsminrev = dfin['Revenue (rounded)'].min()
dfinminrevco = dfin.where(dfin['Revenue (rounded)'] == mninsminrev).dropna()
dfinsminrevco = pd.concat([dfinsminrevco, dfinminrevco], ignore_index=True)
dfinsminrevco = dfinsminrevco.drop(0)
dfinsminrevco[['Industry','State','City','Company','Zip Code','Revenue (rounded)']].sort_values(by='Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[66]:
| Industry | State | City | Company | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|---|
| 0 | Mail, Package and Freight Delivery | Tennessee | Memphis | FedEx | 38120 | 87,700,000,000 |
| 1 | Scientific, Photographic and Control Equipment | Massachusetts | Waltham | Thermo Fisher Scientific | 02451 | 42,900,000,000 |
| 2 | Wholesalers: Electronics and Office Equipment | Arizona | Phoenix | Avnet | 85034 | 23,800,000,000 |
| 3 | Tobacco | Virginia | Richmond | Altria | 23230 | 20,400,000,000 |
| 4 | Energy | Texas | Irving | Vistra | 75039 | 17,200,000,000 |
| 5 | Energy | Massachusetts | Waltham | Global Partners | 02453 | 17,200,000,000 |
| 6 | Waste Management | Arizona | Phoenix | Republic Services | 85054 | 16,000,000,000 |
| 7 | Household and Personal Products | New Jersey | Summit | Kenvue | 07901 | 15,500,000,000 |
| 8 | General Merchandisers | Washington | Seattle | Nordstrom | 98101 | 15,000,000,000 |
| 9 | Insurance: Property and Casualty (Mutual) | Pennsylvania | Erie | Erie Insurance | 16530 | 13,200,000,000 |
| 10 | Computers, Office Equipment | California | San Jose | Western Digital | 95119 | 13,000,000,000 |
| 11 | Health Care: Medical Facilities | Tennessee | Franklin | Community Health Systems | 37067 | 12,600,000,000 |
| 12 | Engineering & Construction | Florida | Coral Gables | MasTec | 33134 | 12,300,000,000 |
| 13 | Railroads | Georgia | Atlanta | Norfolk Southern | 30308 | 12,100,000,000 |
| 14 | Trucking, Truck Leasing | Arkansas | Lowell | J.B. Hunt Transport Services | 72745 | 12,100,000,000 |
| 15 | Hotels, Casinos, Resorts | Virginia | McLean | Hilton | 22102 | 11,200,000,000 |
| 16 | Insurance: Life, Health (Mutual) | Minnesota | Minneapolis | Thrivent Financial for Lutherans | 55415 | 10,900,000,000 |
| 17 | Wholesalers: Health Care | Virginia | Glen Allen | Owens & Minor | 23060 | 10,700,000,000 |
| 18 | Advertising, Marketing | New York | New York | Interpublic | 10022 | 10,700,000,000 |
| 19 | Construction and Farm Machinery | Wisconsin | Oshkosh | Oshkosh | 54902 | 10,700,000,000 |
| 20 | Pipelines | Oklahoma | Tulsa | Williams | 74172 | 10,500,000,000 |
| 21 | Financial Data Services | Georgia | Atlanta | Global Payments | 30326 | 10,100,000,000 |
| 22 | Publishing, Printing | New York | New York | News Corp. | 10036 | 10,100,000,000 |
| 23 | Internet Services and Retailing | Colorado | Englewood | QVC | 80112 | 10,000,000,000 |
| 24 | Motor Vehicles & Parts | Indiana | Elkhart | THOR Industries | 46514 | 10,000,000,000 |
| 25 | Health Care: Pharmacy and Other Services | New Jersey | Secaucus | Quest Diagnostics | 07094 | 9,900,000,000 |
| 26 | Wholesalers: Food and Grocery | Michigan | Byron Center | SpartanNash | 49315 | 9,500,000,000 |
| 27 | Chemicals | Tennessee | Kingsport | Eastman Chemical | 37660 | 9,400,000,000 |
| 28 | Airlines | New York | Long Island City | JetBlue Airways | 11101 | 9,300,000,000 |
| 29 | Pharmaceuticals | New Jersey | Parsippany | Zoetis | 07054 | 9,300,000,000 |
| 30 | Commercial Banks | Ohio | Cleveland | KeyCorp | 44114 | 9,200,000,000 |
| 31 | Health Care: Insurance and Managed Care | New York | New York | Oscar Health | 10013 | 9,200,000,000 |
| 32 | Mining, Crude-Oil Production | Colorado | Denver | Ovintiv | 80202 | 9,200,000,000 |
| 33 | Telecommunications | New York | Long Island City | Altice USA | 11101 | 9,000,000,000 |
| 34 | Oil and Gas Equipment, Services | Texas | Houston | NOV | 77042 | 8,900,000,000 |
| 35 | Apparel | New York | New York | PVH | 10017 | 8,700,000,000 |
| 36 | Securities | California | San Mateo | Franklin Resources | 94403 | 8,500,000,000 |
| 37 | Industrial Machinery | Illinois | Downers Grove | Dover | 60515 | 8,400,000,000 |
| 38 | Computer Software | California | Pleasanton | Workday | 94588 | 8,400,000,000 |
| 39 | Diversified Outsourcing Services | New York | New York | ABM Industries | 10006 | 8,400,000,000 |
| 40 | Packaging, Containers | Illinois | Lake Forest | Packaging Corp. of America | 60045 | 8,400,000,000 |
| 41 | Insurance: Property and Casualty (Stock) | Illinois | Chicago | Old Republic International | 60601 | 8,200,000,000 |
| 42 | Homebuilders | Arizona | Scottsdale | Taylor Morrison Home | 85251 | 8,200,000,000 |
| 43 | Insurance: Life, Health (Stock) | Minnesota | St. Paul | Securian Financial | 55101 | 8,200,000,000 |
| 44 | Transportation and Logistics | Connecticut | Greenwich | XPO | 06831 | 8,100,000,000 |
| 45 | Petroleum Refining | Texas | Houston | Par Pacific | 77024 | 8,000,000,000 |
| 46 | Electronics, Electrical Equip. | Ohio | Westerville | Vertiv s | 43082 | 8,000,000,000 |
| 47 | Real Estate | Ohio | Toledo | Welltower | 43615 | 8,000,000,000 |
| 48 | Network and Other Communications Equipment | California | Santa Clara | Palo Alto Networks | 95054 | 8,000,000,000 |
| 49 | Specialty Retailers: Apparel | New York | New York | Foot Locker | 10001 | 8,000,000,000 |
| 50 | Diversified Financials | New York | New York | Voya Financial | 10169 | 8,000,000,000 |
| 51 | Metals | Texas | Irving | Commercial Metals | 75039 | 7,900,000,000 |
| 52 | Food Consumer Products | Missouri | St. Louis | Post s | 63144 | 7,900,000,000 |
| 53 | Automotive Retailing, Services | Texas | New Braunfels | Rush Enterprises | 78130 | 7,800,000,000 |
| 54 | Medical Products and Equipment | Indiana | Warsaw | Zimmer Biomet s | 46580 | 7,700,000,000 |
| 55 | Food & Drug Stores | Arizona | Phoenix | Sprouts Farmers Market | 85054 | 7,700,000,000 |
| 56 | Home Equipment, Furnishings | Georgia | Atlanta | Newell Brands | 30328 | 7,600,000,000 |
| 57 | Semiconductors and Other Electronic Components | Arizona | Chandler | Microchip Technology | 85224 | 7,600,000,000 |
| 58 | Semiconductors and Other Electronic Components | California | San Jose | Sanmina | 95134 | 7,600,000,000 |
| 59 | Specialty Retailers: Other | Virginia | Richmond | ARKO | 23227 | 7,600,000,000 |
| 60 | Information Technology Services | Virginia | Reston | Science Applications International | 20190 | 7,500,000,000 |
| 61 | Entertainment | California | Beverly Hills | Endeavor | 90210 | 7,500,000,000 |
| 62 | Utilities: Gas and Electric | Michigan | Jackson | CMS Energy | 49201 | 7,500,000,000 |
| 63 | Beverages | California | Corona | Monster Beverage | 92879 | 7,500,000,000 |
| 64 | Food Services | Kentucky | Louisville | Yum Brands | 40213 | 7,500,000,000 |
| 65 | Wholesalers: Diversified | Missouri | St. Louis | Core & Main | 63146 | 7,400,000,000 |
| 66 | Building Materials, Glass | Alabama | Birmingham | Vulcan Materials | 35242 | 7,400,000,000 |
| 67 | Aerospace & Defense | Pennsylvania | Pittsburgh | Howmet Aerospace | 15212 | 7,400,000,000 |
| 68 | Food Production | Illinois | Westchester | Ingredion | 60154 | 7,400,000,000 |
In [67]:
# Join the Dataframe 'gdfusact' with 'dfinsminrevco' for the Smallest Revenue Company in each Industry visualized by City
gdfusactinsminrevco = gdfusact.merge(dfinsminrevco, how = 'inner', on = ['Zip Code'])
gdfusactinsminrevco = gdfusactinsminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [68]:
# Join the Dataframe 'gdfsts' with 'dfinsminrevco' for the Smallest Revenue Company in each Industry visualized by State
gdfstsinsminrevco = gdfsts.merge(dfinsminrevco, how = 'inner', on = ['State'])
gdfstsinsminrevco = gdfstsinsminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [69]:
minsminrc = gdfstsinsminrevco.explore(column='Revenue (rounded)', name='The Smallest Revenue Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsminrevco.explore(m=minsminrc, column='Revenue (rounded)', name='The Smallest Revenue Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsminrc)
minsminrc
Out[69]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [82]:
# Check the Biggest Revenue Industry in US (a.k.a Total Revenue in each Industry)
dfintr = df.groupby('Industry', as_index=False)[['Revenue (rounded)']].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfintr
Out[82]:
| Industry | Revenue (rounded) | |
|---|---|---|
| 0 | Internet Services and Retailing | 1,330,100,000,000 |
| 1 | Commercial Banks | 1,321,000,000,000 |
| 2 | General Merchandisers | 1,116,800,000,000 |
| 3 | Petroleum Refining | 1,044,500,000,000 |
| 4 | Health Care: Insurance and Managed Care | 908,000,000,000 |
| 5 | Wholesalers: Health Care | 853,200,000,000 |
| 6 | Insurance: Property and Casualty (Stock) | 842,900,000,000 |
| 7 | Health Care: Pharmacy and Other Services | 669,500,000,000 |
| 8 | Diversified Financials | 627,600,000,000 |
| 9 | Computers, Office Equipment | 598,300,000,000 |
| 10 | Motor Vehicles & Parts | 590,800,000,000 |
| 11 | Specialty Retailers: Other | 505,200,000,000 |
| 12 | Pharmaceuticals | 487,300,000,000 |
| 13 | Telecommunications | 473,800,000,000 |
| 14 | Semiconductors and Other Electronic Components | 446,900,000,000 |
| 15 | Food & Drug Stores | 441,900,000,000 |
| 16 | Aerospace & Defense | 407,400,000,000 |
| 17 | Computer Software | 393,200,000,000 |
| 18 | Utilities: Gas and Electric | 329,200,000,000 |
| 19 | Insurance: Life, Health (Stock) | 299,200,000,000 |
| 20 | Pipelines | 268,400,000,000 |
| 21 | Food Consumer Products | 263,800,000,000 |
| 22 | Entertainment | 259,900,000,000 |
| 23 | Insurance: Life, Health (Mutual) | 249,800,000,000 |
| 24 | Insurance: Property and Casualty (Mutual) | 226,100,000,000 |
| 25 | Food Production | 222,800,000,000 |
| 26 | Airlines | 221,400,000,000 |
| 27 | Automotive Retailing, Services | 215,700,000,000 |
| 28 | Wholesalers: Food and Grocery | 211,900,000,000 |
| 29 | Mining, Crude-Oil Production | 210,700,000,000 |
| 30 | Industrial Machinery | 207,800,000,000 |
| 31 | Chemicals | 203,000,000,000 |
| 32 | Information Technology Services | 201,900,000,000 |
| 33 | Medical Products and Equipment | 184,600,000,000 |
| 34 | Mail, Package and Freight Delivery | 178,800,000,000 |
| 35 | Securities | 175,900,000,000 |
| 36 | Financial Data Services | 175,300,000,000 |
| 37 | Wholesalers: Diversified | 169,600,000,000 |
| 38 | Energy | 163,200,000,000 |
| 39 | Wholesalers: Electronics and Office Equipment | 158,200,000,000 |
| 40 | Household and Personal Products | 155,300,000,000 |
| 41 | Construction and Farm Machinery | 138,900,000,000 |
| 42 | Health Care: Medical Facilities | 132,500,000,000 |
| 43 | Specialty Retailers: Apparel | 121,800,000,000 |
| 44 | Homebuilders | 119,800,000,000 |
| 45 | Metals | 116,600,000,000 |
| 46 | Food Services | 103,600,000,000 |
| 47 | Engineering & Construction | 100,000,000,000 |
| 48 | Real Estate | 95,100,000,000 |
| 49 | Beverages | 91,600,000,000 |
| 50 | Diversified Outsourcing Services | 89,500,000,000 |
| 51 | Network and Other Communications Equipment | 87,800,000,000 |
| 52 | Packaging, Containers | 80,800,000,000 |
| 53 | Apparel | 79,600,000,000 |
| 54 | Hotels, Casinos, Resorts | 76,100,000,000 |
| 55 | Transportation and Logistics | 60,700,000,000 |
| 56 | Oil and Gas Equipment, Services | 59,600,000,000 |
| 57 | Tobacco | 58,300,000,000 |
| 58 | Railroads | 50,800,000,000 |
| 59 | Electronics, Electrical Equip. | 46,000,000,000 |
| 60 | Scientific, Photographic and Control Equipment | 42,900,000,000 |
| 61 | Waste Management | 38,100,000,000 |
| 62 | Building Materials, Glass | 34,800,000,000 |
| 63 | Advertising, Marketing | 26,400,000,000 |
| 64 | Home Equipment, Furnishings | 26,200,000,000 |
| 65 | Trucking, Truck Leasing | 12,100,000,000 |
| 66 | Publishing, Printing | 10,100,000,000 |
In [83]:
# Join the Dataframe 'gdfusact' with 'dfintr' for the Top 10
dfintr = dfintr.head(10).merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
gdfusactintr = gdfusact.merge(dfintr, how = 'inner', on = ['Zip Code'])
gdfusactintr = gdfusactintr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
# Join the Dataframe 'gdfsts' with 'dfintr'
gdfstsintr = gdfsts.merge(dfintr, how = 'inner', on = ['State'])
gdfstsintr = gdfstsintr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [84]:
# Check what Companies that are in Industry 'Internet Services and Retailing'.
dfintr1st = dfintr.where(dfintr['Industry'] == 'Internet Services and Retailing').dropna()
dfintr1st
Out[84]:
| Industry | Revenue (rounded) | City | State | Company | Zip Code | |
|---|---|---|---|---|---|---|
| 0 | Internet Services and Retailing | 1,330,100,000,000 | Seattle | Washington | Amazon | 98109 |
| 1 | Internet Services and Retailing | 1,330,100,000,000 | Mountain View | California | Alphabet | 94043 |
| 2 | Internet Services and Retailing | 1,330,100,000,000 | Menlo Park | California | Meta | 94025 |
| 3 | Internet Services and Retailing | 1,330,100,000,000 | San Francisco | California | Uber | 94158 |
| 4 | Internet Services and Retailing | 1,330,100,000,000 | Seattle | Washington | Coupang | 98101 |
| 5 | Internet Services and Retailing | 1,330,100,000,000 | Norwalk | Connecticut | Booking s | 06854 |
| 6 | Internet Services and Retailing | 1,330,100,000,000 | Seattle | Washington | Expedia | 98119 |
| 7 | Internet Services and Retailing | 1,330,100,000,000 | Plantation | Florida | Chewy | 33322 |
| 8 | Internet Services and Retailing | 1,330,100,000,000 | Boston | Massachusetts | Wayfair | 02116 |
| 9 | Internet Services and Retailing | 1,330,100,000,000 | San Francisco | California | Airbnb | 94103 |
| 10 | Internet Services and Retailing | 1,330,100,000,000 | San Francisco | California | DoorDash | 94107 |
| 11 | Internet Services and Retailing | 1,330,100,000,000 | San Jose | California | Ebay | 95125 |
| 12 | Internet Services and Retailing | 1,330,100,000,000 | Englewood | Colorado | QVC | 80112 |
In [85]:
# Draw the Map visualizing Total Revenue in each Industry by State and City
minstr = gdfstsintr.explore(column='Revenue (rounded)', name='The Total Revenue in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactintr.explore(m=minstr, column='Revenue (rounded)', name='The Total Revenue in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minstr)
minstr
Out[85]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [86]:
# Draw the Map visualizing the Companies that are in the Biggest Revenue Industry by State and City
gdfstsintr1st = gdfstsintr.where(gdfstsintr['Industry'] == 'Internet Services and Retailing').dropna()
gdfusactintr1st = gdfusactintr.where(gdfusactintr['Industry'] == 'Internet Services and Retailing').dropna()
minstr1st = gdfstsintr1st.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry Companies visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactintr1st.explore(m=minstr1st, column='Revenue (rounded)', name='The Biggest Revenue Industry Companies visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minstr1st)
minstr1st
Out[86]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [76]:
# Check the Average Revenue in each Industry (a.k.a The Biggest Average Revenue Industry in US)
dfinavr = df.groupby('Industry')[df.columns[[7]]].mean('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False)
dfinavr
Out[76]:
| Revenue (rounded) | |
|---|---|
| Industry | |
| Wholesalers: Health Care | 170,640,000,000 |
| General Merchandisers | 159,542,857,143 |
| Health Care: Insurance and Managed Care | 151,333,333,333 |
| Petroleum Refining | 116,055,555,556 |
| Health Care: Pharmacy and Other Services | 111,583,333,333 |
| Internet Services and Retailing | 102,315,384,615 |
| Computers, Office Equipment | 99,716,666,667 |
| Mail, Package and Freight Delivery | 89,400,000,000 |
| Food & Drug Stores | 88,380,000,000 |
| Telecommunications | 67,685,714,286 |
| Commercial Banks | 66,050,000,000 |
| Motor Vehicles & Parts | 59,080,000,000 |
| Computer Software | 56,171,428,571 |
| Insurance: Property and Casualty (Stock) | 46,827,777,778 |
| Insurance: Property and Casualty (Mutual) | 45,220,000,000 |
| Scientific, Photographic and Control Equipment | 42,900,000,000 |
| Wholesalers: Food and Grocery | 42,380,000,000 |
| Diversified Financials | 41,840,000,000 |
| Wholesalers: Electronics and Office Equipment | 39,550,000,000 |
| Pharmaceuticals | 37,484,615,385 |
| Aerospace & Defense | 37,036,363,636 |
| Airlines | 36,900,000,000 |
| Construction and Farm Machinery | 34,725,000,000 |
| Pipelines | 33,550,000,000 |
| Semiconductors and Other Electronic Components | 31,921,428,571 |
| Food Production | 31,828,571,429 |
| Specialty Retailers: Other | 31,575,000,000 |
| Insurance: Life, Health (Mutual) | 31,225,000,000 |
| Household and Personal Products | 31,060,000,000 |
| Tobacco | 29,150,000,000 |
| Entertainment | 28,877,777,778 |
| Energy | 27,200,000,000 |
| Insurance: Life, Health (Stock) | 27,200,000,000 |
| Health Care: Medical Facilities | 26,500,000,000 |
| Food Consumer Products | 21,983,333,333 |
| Network and Other Communications Equipment | 21,950,000,000 |
| Financial Data Services | 21,912,500,000 |
| Mining, Crude-Oil Production | 21,070,000,000 |
| Specialty Retailers: Apparel | 20,300,000,000 |
| Homebuilders | 19,966,666,667 |
| Apparel | 19,900,000,000 |
| Oil and Gas Equipment, Services | 19,866,666,667 |
| Automotive Retailing, Services | 19,609,090,909 |
| Waste Management | 19,050,000,000 |
| Industrial Machinery | 18,890,909,091 |
| Medical Products and Equipment | 18,460,000,000 |
| Beverages | 18,320,000,000 |
| Securities | 17,590,000,000 |
| Food Services | 17,266,666,667 |
| Railroads | 16,933,333,333 |
| Chemicals | 16,916,666,667 |
| Information Technology Services | 16,825,000,000 |
| Engineering & Construction | 16,666,666,667 |
| Metals | 16,657,142,857 |
| Real Estate | 15,850,000,000 |
| Utilities: Gas and Electric | 15,676,190,476 |
| Hotels, Casinos, Resorts | 15,220,000,000 |
| Diversified Outsourcing Services | 14,916,666,667 |
| Wholesalers: Diversified | 14,133,333,333 |
| Advertising, Marketing | 13,200,000,000 |
| Transportation and Logistics | 12,140,000,000 |
| Trucking, Truck Leasing | 12,100,000,000 |
| Building Materials, Glass | 11,600,000,000 |
| Packaging, Containers | 11,542,857,143 |
| Electronics, Electrical Equip. | 11,500,000,000 |
| Publishing, Printing | 10,100,000,000 |
| Home Equipment, Furnishings | 8,733,333,333 |
In [77]:
# Join the Dataframe 'gdfusact' with 'dfinavr' for the Top 10
dfinavrall = dfinavr.merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
dfinavr10 = dfinavr.head(10).merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
gdfusactinavr = gdfusact.merge(dfinavr10, how = 'inner', on = ['Zip Code'])
gdfusactinavr = gdfusactinavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
# Join the Dataframe 'gdfsts' with 'dfinavr'
gdfstsinavr = gdfsts.merge(dfinavr10, how = 'inner', on = ['State'])
gdfstsinavr = gdfstsinavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [78]:
# Fun fact: turns out, there are other Companies that have exactly same ZipCode with McKesson in Irving, Texas.
# The impact on the map, McKesson company even doesn't show up.
dfinavrall.where(dfinavrall['Zip Code'] == '75039').dropna()
Out[78]:
| Industry | Revenue (rounded) | City | State | Company | Zip Code | |
|---|---|---|---|---|---|---|
| 0 | Wholesalers: Health Care | 170,640,000,000 | Irving | Texas | McKesson | 75039 |
| 181 | Construction and Farm Machinery | 34,725,000,000 | Irving | Texas | Caterpillar | 75039 |
| 258 | Energy | 27,200,000,000 | Irving | Texas | Vistra | 75039 |
| 397 | Chemicals | 16,916,666,667 | Irving | Texas | Celanese | 75039 |
| 413 | Engineering & Construction | 16,666,666,667 | Irving | Texas | Fluor | 75039 |
| 423 | Metals | 16,657,142,857 | Irving | Texas | Commercial Metals | 75039 |
| 482 | Building Materials, Glass | 11,600,000,000 | Irving | Texas | Builders FirstSource | 75039 |
In [79]:
# Draw the Map visualizing Average Revenue in each Industry by State and City
minsavr = gdfstsinavr.explore(column='Revenue (rounded)', name='The Average Revenue in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinavr.explore(m=minsavr, column='Revenue (rounded)', name='The Average Revenue in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsavr)
minsavr
Out[79]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [80]:
# Draw the Map visualizing the Companies that are in the Biggest Average Revenue Industry by State and City
gdfstsinavr1st = gdfstsinavr.where(gdfstsinavr['Industry'] == 'Wholesalers: Health Care').dropna()
gdfusactinavr1st = gdfusactinavr.where(gdfusactinavr['Industry'] == 'Wholesalers: Health Care').dropna()
minsavr1st = gdfstsinavr1st.explore(column='Revenue (rounded)', name='The Biggest Average Revenue Industry Companies visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinavr1st.explore(m=minsavr1st, column='Revenue (rounded)', name='The Biggest Average Revenue Industry Companies visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsavr1st)
minsavr1st
Out[80]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [88]:
# Check the Biggest Employer Company in each Industry
dfinsmaxempco = df.head(1)
for ins in inslist[0:]:
dfin = df.where(df['Industry'] == ins[0]).dropna()
mninsmaxemp = dfin['Employees'].max()
dfinmaxempco = dfin.where(dfin['Employees'] == mninsmaxemp).dropna()
dfinsmaxempco = pd.concat([dfinsmaxempco, dfinmaxempco], ignore_index=True)
dfinsmaxempco = dfinsmaxempco.drop(0)
dfinsmaxempco = dfinsmaxempco[['Industry','State','City','Company','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
dfinsmaxempco
Out[88]:
| Industry | State | City | Company | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | General Merchandisers | Arkansas | Bentonville | Walmart | 72712 | 2,100,000 |
| 1 | Internet Services and Retailing | Washington | Seattle | Amazon | 98109 | 1,556,000 |
| 2 | Specialty Retailers: Other | Georgia | Atlanta | Home Depot | 30339 | 470,100 |
| 3 | Information Technology Services | California | Newark | Concentrix | 94560 | 450,000 |
| 4 | Mail, Package and Freight Delivery | Tennessee | Memphis | FedEx | 38120 | 422,100 |
| 5 | Food & Drug Stores | Ohio | Cincinnati | Kroger | 45202 | 409,000 |
| 6 | Health Care: Insurance and Managed Care | Minnesota | Eden Prairie | UnitedHealth | 55344 | 400,000 |
| 7 | Insurance: Property and Casualty (Stock) | Nebraska | Omaha | Berkshire Hathaway | 68131 | 392,400 |
| 8 | Specialty Retailers: Apparel | Massachusetts | Framingham | TJX | 01701 | 364,000 |
| 9 | Food Services | Washington | Seattle | Starbucks | 98134 | 361,000 |
| 10 | Food Consumer Products | New York | Purchase | PepsiCo | 10577 | 319,000 |
| 11 | Commercial Banks | New York | New York | JPMorgan Chase | 10017 | 317,200 |
| 12 | Health Care: Medical Facilities | Tennessee | Nashville | HCA Healthcare | 37203 | 271,000 |
| 13 | Diversified Outsourcing Services | Pennsylvania | Philadelphia | Aramark | 19103 | 266,700 |
| 14 | Health Care: Pharmacy and Other Services | Rhode Island | Woonsocket | CVS Health | 02895 | 259,500 |
| 15 | Computer Software | Washington | Redmond | Microsoft | 98052 | 228,000 |
| 16 | Entertainment | California | Burbank | Walt Disney | 91521 | 205,000 |
| 17 | Aerospace & Defense | Virginia | Arlington | RTX | 22209 | 186,000 |
| 18 | Telecommunications | Pennsylvania | Philadelphia | Comcast | 19103 | 182,000 |
| 19 | Hotels, Casinos, Resorts | Virginia | McLean | Hilton | 22102 | 181,000 |
| 20 | Motor Vehicles & Parts | Michigan | Southfield | Lear | 48033 | 173,700 |
| 21 | Computers, Office Equipment | California | Cupertino | Apple | 95014 | 164,000 |
| 22 | Real Estate | Texas | Dallas | CBRE | 75201 | 140,000 |
| 23 | Pharmaceuticals | New Jersey | New Brunswick | Johnson & Johnson | 08933 | 138,100 |
| 24 | Food Production | Arkansas | Springdale | Tyson Foods | 72762 | 138,000 |
| 25 | Semiconductors and Other Electronic Components | Florida | St. Petersburg | Jabil | 33716 | 138,000 |
| 26 | Airlines | Texas | Fort Worth | American Airlines | 76155 | 133,300 |
| 27 | Transportation and Logistics | Connecticut | Greenwich | GXO Logistics | 06831 | 128,500 |
| 28 | Scientific, Photographic and Control Equipment | Massachusetts | Waltham | Thermo Fisher Scientific | 02451 | 125,000 |
| 29 | Network and Other Communications Equipment | Connecticut | Wallingford | Amphenol | 06492 | 125,000 |
| 30 | Medical Products and Equipment | Illinois | Abbott Park | Abbott Laboratories | 60064 | 114,000 |
| 31 | Construction and Farm Machinery | Texas | Irving | Caterpillar | 75039 | 112,900 |
| 32 | Household and Personal Products | Ohio | Cincinnati | Procter & Gamble | 45202 | 108,000 |
| 33 | Industrial Machinery | North Carolina | Charlotte | Honeywell | 28202 | 102,000 |
| 34 | Diversified Financials | New York | New York | Marsh & McLennan | 10036 | 90,000 |
| 35 | Tobacco | Connecticut | Stamford | Philip Morris | 06901 | 83,100 |
| 36 | Apparel | Oregon | Beaverton | Nike | 97005 | 79,400 |
| 37 | Energy | Massachusetts | Cambridge | GE Vernova | 02141 | 76,800 |
| 38 | Wholesalers: Food and Grocery | Texas | Houston | Sysco | 77077 | 76,000 |
| 39 | Advertising, Marketing | New York | New York | Omnicom | 10017 | 74,900 |
| 40 | Beverages | Georgia | Atlanta | Coca-Cola | 30313 | 69,700 |
| 41 | Insurance: Property and Casualty (Mutual) | Illinois | Bloomington | State Farm | 61710 | 67,400 |
| 42 | Chemicals | Ohio | Cleveland | Sherwin-Williams | 44115 | 63,900 |
| 43 | Wholesalers: Diversified | Georgia | Atlanta | Genuine Parts | 30339 | 63,000 |
| 44 | Waste Management | Texas | Houston | Waste Management | 77002 | 61,700 |
| 45 | Petroleum Refining | Texas | Spring | Exxon Mobil | 77389 | 60,900 |
| 46 | Engineering & Construction | Texas | Houston | Quanta Services | 77008 | 58,400 |
| 47 | Oil and Gas Equipment, Services | Texas | Houston | Baker Hughes | 77079 | 57,000 |
| 48 | Electronics, Electrical Equip. | New York | Corning | Corning | 14831 | 56,300 |
| 49 | Securities | Missouri | Des Peres | Edward Jones | 63131 | 55,000 |
| 50 | Financial Data Services | Florida | Jacksonville | Fidelity National Information | 32202 | 50,000 |
| 51 | Wholesalers: Health Care | Ohio | Dublin | Cardinal Health | 43017 | 48,400 |
| 52 | Insurance: Life, Health (Stock) | New York | New York | MetLife | 10166 | 45,000 |
| 53 | Packaging, Containers | Indiana | Evansville | Berry Global | 47710 | 42,000 |
| 54 | Home Equipment, Furnishings | Georgia | Calhoun | Mohawk Industries | 30701 | 41,900 |
| 55 | Trucking, Truck Leasing | Arkansas | Lowell | J.B. Hunt Transport Services | 72745 | 33,600 |
| 56 | Metals | North Carolina | Charlotte | Nucor | 28211 | 32,700 |
| 57 | Railroads | Nebraska | Omaha | Union Pacific | 68179 | 32,400 |
| 58 | Automotive Retailing, Services | Oregon | Medford | Lithia Motors | 97501 | 30,200 |
| 59 | Building Materials, Glass | Texas | Irving | Builders FirstSource | 75039 | 29,000 |
| 60 | Mining, Crude-Oil Production | Arizona | Phoenix | Freeport-McMoRan | 85004 | 28,500 |
| 61 | Utilities: Gas and Electric | Georgia | Atlanta | Southern | 30308 | 28,500 |
| 62 | Wholesalers: Electronics and Office Equipment | California | Irvine | Ingram Micro | 92612 | 26,100 |
| 63 | Publishing, Printing | New York | New York | News Corp. | 10036 | 23,900 |
| 64 | Pipelines | Texas | Dallas | Energy Transfer | 75225 | 16,200 |
| 65 | Insurance: Life, Health (Mutual) | New York | New York | TIAA | 10017 | 15,600 |
| 66 | Homebuilders | Texas | Arlington | D.R. Horton | 76011 | 14,800 |
In [89]:
# Join the Dataframe 'gdfusact' with 'dfinsmaxempco' for the Biggest Employer Company in each Industry visualized by City
dfinsmaxempco = dfinsmaxempco.head(10)
gdfusactinsmaxempco = gdfusact.merge(dfinsmaxempco, how = 'inner', on = ['Zip Code'])
gdfusactinsmaxempco = gdfusactinsmaxempco.sort_values('Employees', ascending=False).reset_index(drop=True)
# Join the Dataframe 'gdfsts' with 'dfinsmaxempco' for the Biggest Employer Company in each Industry visualized by State
gdfstsinmaxempco = gdfsts.merge(dfinsmaxempco, how = 'inner', on = ['State'])
gdfstsinmaxempco = gdfstsinmaxempco.sort_values('Employees', ascending=False).reset_index(drop=True)
In [90]:
# Draw the Map visualizing the Biggest Employer Company in each Industry by State and City
minsmaxempco = gdfstsinmaxempco.explore(column='Employees', name='The Biggest Employer in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxempco.explore(m=minsmaxempco, column='Employees', name='The Biggest Employer in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxempco)
minsmaxempco
Out[90]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [91]:
# Check the Smallest Employer Company in each Industry
dfinsminempco = df.head(1)
for ins in inslist[0:]:
dfin = df.where(df['Industry'] == ins[0]).dropna()
mninsminemp = dfin['Employees'].min()
dfinminempco = dfin.where(dfin['Employees'] == mninsminemp).dropna()
dfinsminempco = pd.concat([dfinsminempco, dfinminempco], ignore_index=True)
dfinsminempco = dfinsminempco.drop(0)
dfinsminempco = dfinsminempco[['Industry','State','City','Company','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
dfinsminempco
Out[91]:
| Industry | State | City | Company | Zip Code | Employees | |
|---|---|---|---|---|---|---|
| 0 | Mail, Package and Freight Delivery | Georgia | Atlanta | UPS | 30328 | 372,200 |
| 1 | Scientific, Photographic and Control Equipment | Massachusetts | Waltham | Thermo Fisher Scientific | 02451 | 125,000 |
| 2 | Advertising, Marketing | New York | New York | Interpublic | 10022 | 53,300 |
| 3 | Health Care: Medical Facilities | Tennessee | Franklin | Community Health Systems | 37067 | 52,500 |
| 4 | Waste Management | Arizona | Phoenix | Republic Services | 85054 | 42,000 |
| 5 | Hotels, Casinos, Resorts | Nevada | Las Vegas | Las Vegas Sands | 89113 | 40,100 |
| 6 | Health Care: Pharmacy and Other Services | Kentucky | Louisville | BrightSpring Health Services | 40222 | 37,000 |
| 7 | Food & Drug Stores | Arizona | Phoenix | Sprouts Farmers Market | 85054 | 35,000 |
| 8 | Oil and Gas Equipment, Services | Texas | Houston | NOV | 77042 | 34,000 |
| 9 | Trucking, Truck Leasing | Arkansas | Lowell | J.B. Hunt Transport Services | 72745 | 33,600 |
| 10 | General Merchandisers | Massachusetts | Marlborough | BJ's Wholesale Club | 01752 | 33,000 |
| 11 | Food Services | Kentucky | Louisville | Yum Brands | 40213 | 31,700 |
| 12 | Specialty Retailers: Apparel | New York | New York | Foot Locker | 10001 | 30,200 |
| 13 | Electronics, Electrical Equip. | Wisconsin | Milwaukee | Rockwell Automation | 53204 | 27,000 |
| 14 | Engineering & Construction | Texas | Irving | Fluor | 75039 | 26,900 |
| 15 | Diversified Outsourcing Services | Wisconsin | Milwaukee | Manpower | 53212 | 26,700 |
| 16 | Publishing, Printing | New York | New York | News Corp. | 10036 | 23,900 |
| 17 | Wholesalers: Health Care | Virginia | Glen Allen | Owens & Minor | 23060 | 23,200 |
| 18 | Industrial Machinery | District of Columbia | Washington | Xylem | 20003 | 23,000 |
| 19 | Motor Vehicles & Parts | Indiana | Elkhart | THOR Industries | 46514 | 22,300 |
| 20 | Household and Personal Products | New Jersey | Summit | Kenvue | 07901 | 22,000 |
| 21 | Computer Software | California | Pleasanton | Workday | 94588 | 20,500 |
| 22 | Airlines | New York | Long Island City | JetBlue Airways | 11101 | 19,800 |
| 23 | Railroads | Georgia | Atlanta | Norfolk Southern | 30308 | 19,600 |
| 24 | Construction and Farm Machinery | Wisconsin | Oshkosh | Oshkosh | 54902 | 18,500 |
| 25 | Home Equipment, Furnishings | Michigan | Livonia | Masco | 48152 | 18,000 |
| 26 | Commercial Banks | Ohio | Cleveland | KeyCorp | 44114 | 16,800 |
| 27 | Aerospace & Defense | Ohio | Cleveland | TransDigm | 44115 | 16,600 |
| 28 | Medical Products and Equipment | California | Sunnyvale | Intuitive Surgical | 94086 | 15,600 |
| 29 | Wholesalers: Electronics and Office Equipment | Arizona | Phoenix | Avnet | 85034 | 15,500 |
| 30 | Packaging, Containers | Illinois | Lake Forest | Packaging Corp. of America | 60045 | 15,400 |
| 31 | Network and Other Communications Equipment | California | Santa Clara | Palo Alto Networks | 95054 | 15,300 |
| 32 | Semiconductors and Other Electronic Components | California | Milpitas | KLA | 95035 | 15,100 |
| 33 | Apparel | California | Manhattan Beach | Skechers U.S.A. | 90266 | 15,100 |
| 34 | Wholesalers: Food and Grocery | Michigan | Byron Center | SpartanNash | 49315 | 15,000 |
| 35 | Information Technology Services | Arizona | Chandler | Insight Enterprises | 85286 | 14,300 |
| 36 | Transportation and Logistics | Minnesota | Eden Prairie | C.H. Robinson Worldwide | 55347 | 13,800 |
| 37 | Metals | Indiana | Fort Wayne | Steel Dynamics | 46804 | 13,000 |
| 38 | Chemicals | Texas | Irving | Celanese | 75039 | 12,200 |
| 39 | Building Materials, Glass | Alabama | Birmingham | Vulcan Materials | 35242 | 12,000 |
| 40 | Specialty Retailers: Other | Arkansas | El Dorado | Murphy USA | 71730 | 11,600 |
| 41 | Financial Data Services | California | Oakland | Block | 94612 | 11,400 |
| 42 | Telecommunications | New York | Long Island City | Altice USA | 11101 | 10,900 |
| 43 | Food Consumer Products | Minnesota | Arden Hills | Land O'Lakes | 55126 | 9,000 |
| 44 | Food Consumer Products | Ohio | Orrville | J.M. Smucker | 44667 | 9,000 |
| 45 | Automotive Retailing, Services | Texas | New Braunfels | Rush Enterprises | 78130 | 7,900 |
| 46 | Internet Services and Retailing | California | San Francisco | Airbnb | 94103 | 7,300 |
| 47 | Utilities: Gas and Electric | Pennsylvania | Allentown | PPL | 18101 | 6,700 |
| 48 | Insurance: Property and Casualty (Mutual) | Pennsylvania | Erie | Erie Insurance | 16530 | 6,700 |
| 49 | Tobacco | Virginia | Richmond | Altria | 23230 | 6,200 |
| 50 | Pharmaceuticals | Massachusetts | Boston | Vertex Pharmaceuticals | 02210 | 6,100 |
| 51 | Beverages | California | Corona | Monster Beverage | 92879 | 6,000 |
| 52 | Computers, Office Equipment | California | San Jose | Super Micro Computer | 95131 | 5,700 |
| 53 | Insurance: Property and Casualty (Stock) | Ohio | Fairfield | Cincinnati Financial | 45014 | 5,600 |
| 54 | Entertainment | New York | New York | Sirius XM | 10020 | 5,500 |
| 55 | Diversified Financials | New York | New York | StoneX | 10169 | 4,500 |
| 56 | Insurance: Life, Health (Stock) | Missouri | Chesterfield | Reinsurance of America | 63017 | 4,100 |
| 57 | Energy | Massachusetts | Waltham | Global Partners | 02453 | 3,800 |
| 58 | Securities | Connecticut | Greenwich | Interactive Brokers | 06830 | 3,000 |
| 59 | Homebuilders | Arizona | Scottsdale | Taylor Morrison Home | 85251 | 3,000 |
| 60 | Insurance: Life, Health (Mutual) | Ohio | Cincinnati | Western & Southern Financial | 45202 | 2,700 |
| 61 | Health Care: Insurance and Managed Care | New York | New York | Oscar Health | 10013 | 2,400 |
| 62 | Food Production | Ohio | Maumee | Andersons | 43537 | 2,300 |
| 63 | Petroleum Refining | Texas | Houston | Par Pacific | 77024 | 1,800 |
| 64 | Pipelines | Texas | Houston | Cheniere Energy | 77002 | 1,700 |
| 65 | Mining, Crude-Oil Production | Colorado | Denver | Ovintiv | 80202 | 1,600 |
| 66 | Real Estate | Ohio | Toledo | Welltower | 43615 | 700 |
| 67 | Wholesalers: Diversified | California | El Segundo | A-Mark Precious Metals | 90245 | 500 |
In [ ]:
In [92]:
# Join the Dataframe 'gdfusact' with 'dfinsminempco' for the Smallest Employer Company in each Industry visualized by City
dfinsminempco = dfinsminempco.head(10)
gdfusactinsminempco = gdfusact.merge(dfinsminempco, how = 'inner', on = ['Zip Code'])
gdfusactinsminempco = gdfusactinsminempco.sort_values('Employees', ascending=False).reset_index(drop=True)
# Join the Dataframe 'gdfsts' with 'dfinsminempco' for the Smallest Employer Company in each Industry visualized by State
gdfstsinminempco = gdfsts.merge(dfinsminempco, how = 'inner', on = ['State'])
gdfstsinminempco = gdfstsinminempco.sort_values('Employees', ascending=False).reset_index(drop=True)
In [93]:
minsminempco = gdfstsinminempco.explore(column='Employees', name='The Smallest Employer Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsminempco.explore(m=minsminempco, column='Employees', name='The Smallest Employer Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsminempco)
minsminempco
Out[93]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [94]:
# Check the Biggest Revenue Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Revenue (rounded)': [1],
'State': ['Dummy'],
'Industry': ['Dummy']}
dfstmaxrevin = pd.DataFrame(dummy)
dfst = None
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
#print(dfst)
dfstmaxrevin = pd.concat([dfstmaxrevin, dfst.groupby(['State','Industry'], as_index=False).sum("Revenue (rounded)").sort_values(by=['Revenue (rounded)'], ascending=False)[['State','Industry','Revenue (rounded)']].head(1)])
dfstmaxrevin = dfstmaxrevin.iloc[1:]
dfstmaxrevin = dfstmaxrevin[['State','Industry','Revenue (rounded)']].sort_values(by=['Revenue (rounded)'], ascending=False).reset_index(drop=True)
dfstmaxrevin
Out[94]:
| State | Industry | Revenue (rounded) | |
|---|---|---|---|
| 0 | Texas | Petroleum Refining | 858,500,000,000 |
| 1 | New York | Commercial Banks | 737,300,000,000 |
| 2 | Washington | Internet Services and Retailing | 682,000,000,000 |
| 3 | Arkansas | General Merchandisers | 681,000,000,000 |
| 4 | California | Internet Services and Retailing | 590,600,000,000 |
| 5 | Michigan | Motor Vehicles & Parts | 420,200,000,000 |
| 6 | Minnesota | Health Care: Insurance and Managed Care | 400,300,000,000 |
| 7 | Rhode Island | Health Care: Pharmacy and Other Services | 372,800,000,000 |
| 8 | Nebraska | Insurance: Property and Casualty (Stock) | 371,400,000,000 |
| 9 | Pennsylvania | Wholesalers: Health Care | 294,000,000,000 |
| 10 | Virginia | Aerospace & Defense | 247,400,000,000 |
| 11 | Connecticut | Health Care: Pharmacy and Other Services | 247,100,000,000 |
| 12 | North Carolina | Commercial Banks | 233,000,000,000 |
| 13 | Ohio | Wholesalers: Health Care | 226,800,000,000 |
| 14 | New Jersey | Pharmaceuticals | 210,600,000,000 |
| 15 | Indiana | Health Care: Insurance and Managed Care | 177,000,000,000 |
| 16 | Missouri | Health Care: Insurance and Managed Care | 163,100,000,000 |
| 17 | Georgia | Specialty Retailers: Other | 159,500,000,000 |
| 18 | District of Columbia | Diversified Financials | 152,700,000,000 |
| 19 | Illinois | Food & Drug Stores | 147,700,000,000 |
| 20 | Kentucky | Health Care: Insurance and Managed Care | 117,800,000,000 |
| 21 | Tennessee | Mail, Package and Freight Delivery | 87,700,000,000 |
| 22 | Idaho | Food & Drug Stores | 79,200,000,000 |
| 23 | Maryland | Aerospace & Defense | 71,000,000,000 |
| 24 | Florida | Food & Drug Stores | 60,200,000,000 |
| 25 | Massachusetts | Specialty Retailers: Apparel | 56,400,000,000 |
| 26 | Oregon | Apparel | 51,400,000,000 |
| 27 | Wisconsin | Insurance: Life, Health (Mutual) | 41,400,000,000 |
| 28 | Nevada | Hotels, Casinos, Resorts | 39,800,000,000 |
| 29 | Oklahoma | Pipelines | 32,200,000,000 |
| 30 | Colorado | Mining, Crude-Oil Production | 27,900,000,000 |
| 31 | Arizona | Mining, Crude-Oil Production | 25,500,000,000 |
| 32 | Iowa | Insurance: Life, Health (Stock) | 16,100,000,000 |
| 33 | Louisiana | Telecommunications | 13,100,000,000 |
| 34 | Delaware | Chemicals | 12,400,000,000 |
| 35 | Alabama | Commercial Banks | 9,400,000,000 |
| 36 | Kansas | Food Production | 9,100,000,000 |
In [ ]:
# Conclusion: the Biggest Revenue Industry is Petroleum Refining
In [95]:
dfstmaxrevin = dfstmaxrevin.head(10)
dfstmaxrevin = dfstmaxrevin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxrevin = dfstmaxrevin[['State','Industry','Company','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfstmaxrevin
Out[95]:
| State | Industry | Company | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|
| 0 | Texas | Petroleum Refining | Exxon Mobil | 77389 | 858,500,000,000 |
| 1 | Texas | Petroleum Refining | Chevron | 77002 | 858,500,000,000 |
| 2 | Texas | Petroleum Refining | Phillips 66 | 77042 | 858,500,000,000 |
| 3 | Texas | Petroleum Refining | Valero Energy | 78249 | 858,500,000,000 |
| 4 | Texas | Petroleum Refining | HF Sinclair | 75219 | 858,500,000,000 |
| 5 | Texas | Petroleum Refining | Par Pacific | 77024 | 858,500,000,000 |
| 6 | New York | Commercial Banks | JPMorgan Chase | 10017 | 737,300,000,000 |
| 7 | New York | Commercial Banks | Citi | 10013 | 737,300,000,000 |
| 8 | New York | Commercial Banks | Goldman Sachs | 10282 | 737,300,000,000 |
| 9 | New York | Commercial Banks | Morgan Stanley | 10036 | 737,300,000,000 |
| 10 | New York | Commercial Banks | Bank of New York | 10286 | 737,300,000,000 |
| 11 | New York | Commercial Banks | M&T Bank | 14203 | 737,300,000,000 |
| 12 | Washington | Internet Services and Retailing | Amazon | 98109 | 682,000,000,000 |
| 13 | Washington | Internet Services and Retailing | Coupang | 98101 | 682,000,000,000 |
| 14 | Washington | Internet Services and Retailing | Expedia | 98119 | 682,000,000,000 |
| 15 | Arkansas | General Merchandisers | Walmart | 72712 | 681,000,000,000 |
| 16 | California | Internet Services and Retailing | Alphabet | 94043 | 590,600,000,000 |
| 17 | California | Internet Services and Retailing | Meta | 94025 | 590,600,000,000 |
| 18 | California | Internet Services and Retailing | Uber | 94158 | 590,600,000,000 |
| 19 | California | Internet Services and Retailing | Airbnb | 94103 | 590,600,000,000 |
| 20 | California | Internet Services and Retailing | DoorDash | 94107 | 590,600,000,000 |
| 21 | California | Internet Services and Retailing | Ebay | 95125 | 590,600,000,000 |
| 22 | Michigan | Motor Vehicles & Parts | General Motors | 48265 | 420,200,000,000 |
| 23 | Michigan | Motor Vehicles & Parts | Ford Motor | 48126 | 420,200,000,000 |
| 24 | Michigan | Motor Vehicles & Parts | Lear | 48033 | 420,200,000,000 |
| 25 | Michigan | Motor Vehicles & Parts | BorgWarner | 48326 | 420,200,000,000 |
| 26 | Michigan | Motor Vehicles & Parts | Autoliv | 48326 | 420,200,000,000 |
| 27 | Minnesota | Health Care: Insurance and Managed Care | UnitedHealth | 55344 | 400,300,000,000 |
| 28 | Rhode Island | Health Care: Pharmacy and Other Services | CVS Health | 02895 | 372,800,000,000 |
| 29 | Nebraska | Insurance: Property and Casualty (Stock) | Berkshire Hathaway | 68131 | 371,400,000,000 |
| 30 | Pennsylvania | Wholesalers: Health Care | Cencora | 19428 | 294,000,000,000 |
In [96]:
gdfstsmaxrevin = gdfsts.merge(dfstmaxrevin, how = 'inner', on = ['State'])
gdfusactmaxrevin = gdfusact.merge(dfstmaxrevin, how = 'inner', on = ['Zip Code'])
gdfusactmaxrevin
mstmaxrevin = gdfstsmaxrevin.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactmaxrevin.explore(m=mstmaxrevin, column='Revenue (rounded)', name='The Biggest Revenue Company in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxrevin)
mstmaxrevin
Out[96]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [99]:
# Check the Smallest Revenue Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Revenue (rounded)': [1],
'State': ['Dummy'],
'Industry': ['Dummy']}
dfstminrevin = pd.DataFrame(dummy)
dfst = None
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfstminrevin = pd.concat([dfstminrevin, dfst.groupby(['State','Industry'], as_index=False).sum("Revenue (rounded)").sort_values(by=['Revenue (rounded)'], ascending=True)[['State','Industry','Revenue (rounded)']].head(1)])
dfstminrevin = dfstminrevin.iloc[1:]
dfstminrevin[['State','Industry','Revenue (rounded)']].sort_values(by=['Revenue (rounded)'], ascending=False).reset_index(drop=True)
Out[99]:
| State | Industry | Revenue (rounded) | |
|---|---|---|---|
| 0 | Nevada | Hotels, Casinos, Resorts | 39,800,000,000 |
| 1 | Oregon | Automotive Retailing, Services | 36,600,000,000 |
| 2 | Idaho | Semiconductors and Other Electronic Components | 25,100,000,000 |
| 3 | Maryland | Energy | 23,600,000,000 |
| 4 | Oklahoma | Mining, Crude-Oil Production | 15,900,000,000 |
| 5 | Iowa | Specialty Retailers: Other | 14,900,000,000 |
| 6 | Nebraska | Insurance: Life, Health (Mutual) | 14,600,000,000 |
| 7 | North Carolina | Automotive Retailing, Services | 14,200,000,000 |
| 8 | Delaware | Chemicals | 12,400,000,000 |
| 9 | Arkansas | Trucking, Truck Leasing | 12,100,000,000 |
| 10 | Louisiana | Utilities: Gas and Electric | 11,900,000,000 |
| 11 | Virginia | Homebuilders | 10,700,000,000 |
| 12 | Washington | Specialty Retailers: Apparel | 10,600,000,000 |
| 13 | Rhode Island | Insurance: Property and Casualty (Stock) | 10,400,000,000 |
| 14 | Colorado | Internet Services and Retailing | 10,000,000,000 |
| 15 | New Jersey | Food Consumer Products | 9,600,000,000 |
| 16 | Tennessee | Chemicals | 9,400,000,000 |
| 17 | Connecticut | Securities | 9,400,000,000 |
| 18 | Massachusetts | Semiconductors and Other Electronic Components | 9,400,000,000 |
| 19 | Kansas | Food Production | 9,100,000,000 |
| 20 | Georgia | Packaging, Containers | 8,800,000,000 |
| 21 | District of Columbia | Industrial Machinery | 8,600,000,000 |
| 22 | Illinois | Packaging, Containers | 8,400,000,000 |
| 23 | Wisconsin | Electronics, Electrical Equip. | 8,300,000,000 |
| 24 | Ohio | Electronics, Electrical Equip. | 8,000,000,000 |
| 25 | New York | Specialty Retailers: Apparel | 8,000,000,000 |
| 26 | Missouri | Food Consumer Products | 7,900,000,000 |
| 27 | Michigan | Home Equipment, Furnishings | 7,800,000,000 |
| 28 | Indiana | Medical Products and Equipment | 7,700,000,000 |
| 29 | Texas | Information Technology Services | 7,700,000,000 |
| 30 | Arizona | Semiconductors and Other Electronic Components | 7,600,000,000 |
| 31 | Florida | Wholesalers: Diversified | 7,600,000,000 |
| 32 | Kentucky | Food Services | 7,500,000,000 |
| 33 | California | Beverages | 7,500,000,000 |
| 34 | Minnesota | Wholesalers: Diversified | 7,500,000,000 |
| 35 | Pennsylvania | Aerospace & Defense | 7,400,000,000 |
| 36 | Alabama | Building Materials, Glass | 7,400,000,000 |
In [100]:
dfstminrevin = dfstminrevin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstminrevin = dfstminrevin[['State','Industry','Company','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfstminrevin
Out[100]:
| State | Industry | Company | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|
| 0 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International | 89109 | 39,800,000,000 |
| 1 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment | 89501 | 39,800,000,000 |
| 2 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands | 89113 | 39,800,000,000 |
| 3 | Oregon | Automotive Retailing, Services | Lithia Motors | 97501 | 36,600,000,000 |
| 4 | Idaho | Semiconductors and Other Electronic Components | Micron Technology | 83716 | 25,100,000,000 |
| 5 | Maryland | Energy | Constellation Energy | 21231 | 23,600,000,000 |
| 6 | Oklahoma | Mining, Crude-Oil Production | Devon Energy | 73102 | 15,900,000,000 |
| 7 | Iowa | Specialty Retailers: Other | Casey's General Stores | 50021 | 14,900,000,000 |
| 8 | Nebraska | Insurance: Life, Health (Mutual) | Mutual of Omaha Insurance | 68175 | 14,600,000,000 |
| 9 | North Carolina | Automotive Retailing, Services | Sonic Automotive | 28211 | 14,200,000,000 |
| 10 | Delaware | Chemicals | DuPont | 19805 | 12,400,000,000 |
| 11 | Arkansas | Trucking, Truck Leasing | J.B. Hunt Transport Services | 72745 | 12,100,000,000 |
| 12 | Louisiana | Utilities: Gas and Electric | Entergy | 70113 | 11,900,000,000 |
| 13 | Virginia | Homebuilders | NVR | 20190 | 10,700,000,000 |
| 14 | Washington | Specialty Retailers: Apparel | Lululemon athletica | 98390 | 10,600,000,000 |
| 15 | Rhode Island | Insurance: Property and Casualty (Stock) | FM | 02919 | 10,400,000,000 |
| 16 | Colorado | Internet Services and Retailing | QVC | 80112 | 10,000,000,000 |
| 17 | New Jersey | Food Consumer Products | Campbell's | 08103 | 9,600,000,000 |
| 18 | Tennessee | Chemicals | Eastman Chemical | 37660 | 9,400,000,000 |
| 19 | Connecticut | Securities | Interactive Brokers | 06830 | 9,400,000,000 |
| 20 | Massachusetts | Semiconductors and Other Electronic Components | Analog Devices | 01887 | 9,400,000,000 |
| 21 | Kansas | Food Production | Seaboard | 66202 | 9,100,000,000 |
| 22 | Georgia | Packaging, Containers | Graphic Packaging | 30328 | 8,800,000,000 |
| 23 | District of Columbia | Industrial Machinery | Xylem | 20003 | 8,600,000,000 |
| 24 | Illinois | Packaging, Containers | Packaging Corp. of America | 60045 | 8,400,000,000 |
| 25 | Wisconsin | Electronics, Electrical Equip. | Rockwell Automation | 53204 | 8,300,000,000 |
| 26 | New York | Specialty Retailers: Apparel | Foot Locker | 10001 | 8,000,000,000 |
| 27 | Ohio | Electronics, Electrical Equip. | Vertiv s | 43082 | 8,000,000,000 |
| 28 | Missouri | Food Consumer Products | Post s | 63144 | 7,900,000,000 |
| 29 | Michigan | Home Equipment, Furnishings | Masco | 48152 | 7,800,000,000 |
| 30 | Indiana | Medical Products and Equipment | Zimmer Biomet s | 46580 | 7,700,000,000 |
| 31 | Texas | Information Technology Services | KBR | 77002 | 7,700,000,000 |
| 32 | Arizona | Semiconductors and Other Electronic Components | Microchip Technology | 85224 | 7,600,000,000 |
| 33 | Florida | Wholesalers: Diversified | Watsco | 33133 | 7,600,000,000 |
| 34 | California | Beverages | Monster Beverage | 92879 | 7,500,000,000 |
| 35 | Minnesota | Wholesalers: Diversified | Fastenal | 55987 | 7,500,000,000 |
| 36 | Kentucky | Food Services | Yum Brands | 40213 | 7,500,000,000 |
| 37 | Pennsylvania | Aerospace & Defense | Howmet Aerospace | 15212 | 7,400,000,000 |
| 38 | Alabama | Building Materials, Glass | Vulcan Materials | 35242 | 7,400,000,000 |
In [101]:
gdfstsminrevin = gdfsts.merge(dfstminrevin, how = 'inner', on = ['State'])
gdfusactminrevin = gdfusact.merge(dfstminrevin, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactminrevin
Out[101]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Industry | Company | Revenue (rounded) | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 89501 | 40 | -120 | 3,641 | POINT (-119.81262 39.52602) | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment | 39,800,000,000 |
| 1 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands | 39,800,000,000 |
| 2 | 89109 | 36 | -115 | 6,924 | POINT (-115.16327 36.12603) | Nevada | Hotels, Casinos, Resorts | MGM Resorts International | 39,800,000,000 |
| 3 | 97501 | 42 | -123 | 45,008 | POINT (-122.89459 42.2856) | Oregon | Automotive Retailing, Services | Lithia Motors | 36,600,000,000 |
| 4 | 83716 | 44 | -116 | 21,091 | POINT (-115.6548 43.67271) | Idaho | Semiconductors and Other Electronic Components | Micron Technology | 25,100,000,000 |
| 5 | 21231 | 39 | -77 | 14,556 | POINT (-76.592 39.28775) | Maryland | Energy | Constellation Energy | 23,600,000,000 |
| 6 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Oklahoma | Mining, Crude-Oil Production | Devon Energy | 15,900,000,000 |
| 7 | 50021 | 42 | -94 | 29,718 | POINT (-93.56838 41.7207) | Iowa | Specialty Retailers: Other | Casey's General Stores | 14,900,000,000 |
| 8 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | Nebraska | Insurance: Life, Health (Mutual) | Mutual of Omaha Insurance | 14,600,000,000 |
| 9 | 28211 | 35 | -81 | 32,637 | POINT (-80.79604 35.16816) | North Carolina | Automotive Retailing, Services | Sonic Automotive | 14,200,000,000 |
| 10 | 19805 | 40 | -76 | 40,315 | POINT (-75.59373 39.74523) | Delaware | Chemicals | DuPont | 12,400,000,000 |
| 11 | 72745 | 36 | -94 | 14,521 | POINT (-94.10046 36.2477) | Arkansas | Trucking, Truck Leasing | J.B. Hunt Transport Services | 12,100,000,000 |
| 12 | 70113 | 30 | -90 | 9,888 | POINT (-90.08382 29.9422) | Louisiana | Utilities: Gas and Electric | Entergy | 11,900,000,000 |
| 13 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | Homebuilders | NVR | 10,700,000,000 |
| 14 | 98390 | 47 | -122 | 11,497 | POINT (-122.22894 47.21195) | Washington | Specialty Retailers: Apparel | Lululemon athletica | 10,600,000,000 |
| 15 | 02919 | 42 | -72 | 29,473 | POINT (-71.52002 41.82733) | Rhode Island | Insurance: Property and Casualty (Stock) | FM | 10,400,000,000 |
| 16 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Colorado | Internet Services and Retailing | QVC | 10,000,000,000 |
| 17 | 08103 | 40 | -75 | 13,137 | POINT (-75.11275 39.93533) | New Jersey | Food Consumer Products | Campbell's | 9,600,000,000 |
| 18 | 06830 | 41 | -74 | 24,919 | POINT (-73.624 41.048) | Connecticut | Securities | Interactive Brokers | 9,400,000,000 |
| 19 | 01887 | 43 | -71 | 23,195 | POINT (-71.16541 42.56091) | Massachusetts | Semiconductors and Other Electronic Components | Analog Devices | 9,400,000,000 |
| 20 | 37660 | 37 | -83 | 40,114 | POINT (-82.57339 36.52938) | Tennessee | Chemicals | Eastman Chemical | 9,400,000,000 |
| 21 | 66202 | 39 | -95 | 17,321 | POINT (-94.66909 39.02392) | Kansas | Food Production | Seaboard | 9,100,000,000 |
| 22 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | Packaging, Containers | Graphic Packaging | 8,800,000,000 |
| 23 | 20003 | 39 | -77 | 36,194 | POINT (-76.99033 38.88193) | District of Columbia | Industrial Machinery | Xylem | 8,600,000,000 |
| 24 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Illinois | Packaging, Containers | Packaging Corp. of America | 8,400,000,000 |
| 25 | 53204 | 43 | -88 | 40,008 | POINT (-87.92552 43.01806) | Wisconsin | Electronics, Electrical Equip. | Rockwell Automation | 8,300,000,000 |
| 26 | 43082 | 40 | -83 | 33,799 | POINT (-82.88437 40.15537) | Ohio | Electronics, Electrical Equip. | Vertiv s | 8,000,000,000 |
| 27 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | Specialty Retailers: Apparel | Foot Locker | 8,000,000,000 |
| 28 | 63144 | 39 | -90 | 9,580 | POINT (-90.3482 38.61943) | Missouri | Food Consumer Products | Post s | 7,900,000,000 |
| 29 | 48152 | 42 | -83 | 30,394 | POINT (-83.37433 42.42597) | Michigan | Home Equipment, Furnishings | Masco | 7,800,000,000 |
| 30 | 46580 | 41 | -86 | 21,812 | POINT (-85.87212 41.20884) | Indiana | Medical Products and Equipment | Zimmer Biomet s | 7,700,000,000 |
| 31 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Information Technology Services | KBR | 7,700,000,000 |
| 32 | 85224 | 33 | -112 | 48,304 | POINT (-111.87616 33.32351) | Arizona | Semiconductors and Other Electronic Components | Microchip Technology | 7,600,000,000 |
| 33 | 33133 | 26 | -80 | 34,651 | POINT (-80.24327 25.72983) | Florida | Wholesalers: Diversified | Watsco | 7,600,000,000 |
| 34 | 55987 | 44 | -92 | 33,911 | POINT (-91.63143 43.98469) | Minnesota | Wholesalers: Diversified | Fastenal | 7,500,000,000 |
| 35 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | California | Beverages | Monster Beverage | 7,500,000,000 |
| 36 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | Kentucky | Food Services | Yum Brands | 7,500,000,000 |
| 37 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pennsylvania | Aerospace & Defense | Howmet Aerospace | 7,400,000,000 |
| 38 | 35242 | 33 | -87 | 56,956 | POINT (-86.67073 33.42371) | Alabama | Building Materials, Glass | Vulcan Materials | 7,400,000,000 |
In [102]:
mstminrevin = gdfstsminrevin.explore(column='Revenue (rounded)', name='The Smallest Revenue Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactminrevin.explore(m=mstminrevin, column='Revenue (rounded)', name='The Smallest Revenue Company in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstminrevin)
mstminrevin
Out[102]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [103]:
# Check the Biggest Employer Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Employees': [1],
'State': ['Dummy'],
'Industry': ['Dummy']}
dfstmaxempin = pd.DataFrame(dummy)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfstmaxempin = pd.concat([dfstmaxempin, dfst.groupby(['State','Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'],
ascending=False)[['State','Industry','Employees']].head(1)])
dfstmaxempin = dfstmaxempin.iloc[1:]
dfstmaxempin[['State','Industry','Employees']].sort_values(by=['Employees'], ascending=False).reset_index(drop=True)
Out[103]:
| State | Industry | Employees | |
|---|---|---|---|
| 0 | Arkansas | General Merchandisers | 2,100,000 |
| 1 | Washington | Internet Services and Retailing | 1,667,500 |
| 2 | New York | Commercial Banks | 746,000 |
| 3 | Virginia | Aerospace & Defense | 616,000 |
| 4 | Michigan | Motor Vehicles & Parts | 607,300 |
| 5 | Georgia | Specialty Retailers: Other | 470,100 |
| 6 | California | Information Technology Services | 450,000 |
| 7 | Minnesota | General Merchandisers | 440,000 |
| 8 | Tennessee | Mail, Package and Freight Delivery | 422,100 |
| 9 | Ohio | Food & Drug Stores | 409,000 |
| 10 | Nebraska | Insurance: Property and Casualty (Stock) | 392,400 |
| 11 | Massachusetts | Specialty Retailers: Apparel | 364,000 |
| 12 | New Jersey | Information Technology Services | 336,800 |
| 13 | North Carolina | Commercial Banks | 268,100 |
| 14 | Pennsylvania | Diversified Outsourcing Services | 266,700 |
| 15 | Rhode Island | Health Care: Pharmacy and Other Services | 259,500 |
| 16 | Florida | Food & Drug Stores | 255,000 |
| 17 | Illinois | Food & Drug Stores | 252,500 |
| 18 | Texas | Food Services | 245,500 |
| 19 | Idaho | Food & Drug Stores | 196,600 |
| 20 | Connecticut | Transportation and Logistics | 168,000 |
| 21 | Nevada | Hotels, Casinos, Resorts | 159,100 |
| 22 | Maryland | Hotels, Casinos, Resorts | 155,000 |
| 23 | Indiana | Health Care: Insurance and Managed Care | 103,700 |
| 24 | Missouri | Specialty Retailers: Other | 85,600 |
| 25 | Oregon | Apparel | 79,400 |
| 26 | Colorado | Health Care: Medical Facilities | 76,000 |
| 27 | Kentucky | Health Care: Insurance and Managed Care | 65,700 |
| 28 | District of Columbia | Medical Products and Equipment | 62,000 |
| 29 | Wisconsin | General Merchandisers | 60,000 |
| 30 | Arizona | Waste Management | 42,000 |
| 31 | Iowa | Specialty Retailers: Other | 33,100 |
| 32 | Louisiana | Telecommunications | 25,000 |
| 33 | Delaware | Chemicals | 24,000 |
| 34 | Alabama | Commercial Banks | 19,600 |
| 35 | Kansas | Food Production | 14,000 |
| 36 | Oklahoma | Pipelines | 11,000 |
In [ ]:
# Conclusion: the Biggest Employer Industry is General Merchandisers.
In [104]:
dfstmaxempin = dfstmaxempin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxempin[['State','Industry','Company','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[104]:
| State | Industry | Company | Zip Code | Employees | |
|---|---|---|---|---|---|
| 0 | Arkansas | General Merchandisers | Walmart | 72712 | 2,100,000 |
| 1 | Washington | Internet Services and Retailing | Amazon | 98109 | 1,667,500 |
| 2 | Washington | Internet Services and Retailing | Coupang | 98101 | 1,667,500 |
| 3 | Washington | Internet Services and Retailing | Expedia | 98119 | 1,667,500 |
| 4 | New York | Commercial Banks | M&T Bank | 14203 | 746,000 |
| 5 | New York | Commercial Banks | Bank of New York | 10286 | 746,000 |
| 6 | New York | Commercial Banks | Morgan Stanley | 10036 | 746,000 |
| 7 | New York | Commercial Banks | Goldman Sachs | 10282 | 746,000 |
| 8 | New York | Commercial Banks | Citi | 10013 | 746,000 |
| 9 | New York | Commercial Banks | JPMorgan Chase | 10017 | 746,000 |
| 10 | Virginia | Aerospace & Defense | RTX | 22209 | 616,000 |
| 11 | Virginia | Aerospace & Defense | Boeing | 22202 | 616,000 |
| 12 | Virginia | Aerospace & Defense | General Dynamics | 20190 | 616,000 |
| 13 | Virginia | Aerospace & Defense | Northrop Grumman | 22042 | 616,000 |
| 14 | Virginia | Aerospace & Defense | Huntington Ingalls Industries | 23607 | 616,000 |
| 15 | Michigan | Motor Vehicles & Parts | General Motors | 48265 | 607,300 |
| 16 | Michigan | Motor Vehicles & Parts | Autoliv | 48326 | 607,300 |
| 17 | Michigan | Motor Vehicles & Parts | BorgWarner | 48326 | 607,300 |
| 18 | Michigan | Motor Vehicles & Parts | Lear | 48033 | 607,300 |
| 19 | Michigan | Motor Vehicles & Parts | Ford Motor | 48126 | 607,300 |
| 20 | Georgia | Specialty Retailers: Other | Home Depot | 30339 | 470,100 |
| 21 | California | Information Technology Services | Concentrix | 94560 | 450,000 |
| 22 | Minnesota | General Merchandisers | Target | 55403 | 440,000 |
| 23 | Tennessee | Mail, Package and Freight Delivery | FedEx | 38120 | 422,100 |
| 24 | Ohio | Food & Drug Stores | Kroger | 45202 | 409,000 |
| 25 | Nebraska | Insurance: Property and Casualty (Stock) | Berkshire Hathaway | 68131 | 392,400 |
| 26 | Massachusetts | Specialty Retailers: Apparel | TJX | 01701 | 364,000 |
| 27 | New Jersey | Information Technology Services | Cognizant Technology | 07666 | 336,800 |
| 28 | North Carolina | Commercial Banks | Truist Financial | 28202 | 268,100 |
| 29 | North Carolina | Commercial Banks | First Citizens BancShares | 27609 | 268,100 |
| 30 | North Carolina | Commercial Banks | Bank of America | 28255 | 268,100 |
| 31 | Pennsylvania | Diversified Outsourcing Services | Aramark | 19103 | 266,700 |
| 32 | Rhode Island | Health Care: Pharmacy and Other Services | CVS Health | 02895 | 259,500 |
| 33 | Florida | Food & Drug Stores | Publix Super Markets | 33811 | 255,000 |
| 34 | Illinois | Food & Drug Stores | Walgreens | 60015 | 252,500 |
| 35 | Texas | Food Services | Yum China s | 75074 | 245,500 |
| 36 | Idaho | Food & Drug Stores | Albertsons | 83706 | 196,600 |
| 37 | Connecticut | Transportation and Logistics | XPO | 06831 | 168,000 |
| 38 | Connecticut | Transportation and Logistics | GXO Logistics | 06831 | 168,000 |
| 39 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment | 89501 | 159,100 |
| 40 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands | 89113 | 159,100 |
| 41 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International | 89109 | 159,100 |
| 42 | Maryland | Hotels, Casinos, Resorts | Marriott International | 20814 | 155,000 |
| 43 | Indiana | Health Care: Insurance and Managed Care | Elevance Health | 46204 | 103,700 |
| 44 | Missouri | Specialty Retailers: Other | O'Reilly Automotive | 65802 | 85,600 |
| 45 | Oregon | Apparel | Nike | 97005 | 79,400 |
| 46 | Colorado | Health Care: Medical Facilities | DaVita | 80202 | 76,000 |
| 47 | Kentucky | Health Care: Insurance and Managed Care | Humana | 40202 | 65,700 |
| 48 | District of Columbia | Medical Products and Equipment | Danaher | 20037 | 62,000 |
| 49 | Wisconsin | General Merchandisers | Kohl's | 53051 | 60,000 |
| 50 | Arizona | Waste Management | Republic Services | 85054 | 42,000 |
| 51 | Iowa | Specialty Retailers: Other | Casey's General Stores | 50021 | 33,100 |
| 52 | Louisiana | Telecommunications | Lumen Technologies | 71203 | 25,000 |
| 53 | Delaware | Chemicals | DuPont | 19805 | 24,000 |
| 54 | Alabama | Commercial Banks | Regions Financial | 35203 | 19,600 |
| 55 | Kansas | Food Production | Seaboard | 66202 | 14,000 |
| 56 | Oklahoma | Pipelines | Williams | 74172 | 11,000 |
| 57 | Oklahoma | Pipelines | Oneok | 74103 | 11,000 |
In [105]:
gdfstsmaxempin = gdfsts.merge(dfstmaxempin, how = 'inner', on = ['State'])
gdfusactmaxempin = gdfusact.merge(dfstmaxempin, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactmaxempin
Out[105]:
| Zip Code | Latitude | Longitude | Population | geometry | Employees | State | Industry | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | 2,100,000 | Arkansas | General Merchandisers | Walmart |
| 1 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | 1,667,500 | Washington | Internet Services and Retailing | Expedia |
| 2 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | 1,667,500 | Washington | Internet Services and Retailing | Amazon |
| 3 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | 1,667,500 | Washington | Internet Services and Retailing | Coupang |
| 4 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | 746,000 | New York | Commercial Banks | Goldman Sachs |
| 5 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | 746,000 | New York | Commercial Banks | Bank of New York |
| 6 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | 746,000 | New York | Commercial Banks | Citi |
| 7 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | 746,000 | New York | Commercial Banks | JPMorgan Chase |
| 8 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | 746,000 | New York | Commercial Banks | Morgan Stanley |
| 9 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | 746,000 | New York | Commercial Banks | M&T Bank |
| 10 | 23607 | 37 | -76 | 23,028 | POINT (-76.42235 36.98753) | 616,000 | Virginia | Aerospace & Defense | Huntington Ingalls Industries |
| 11 | 22042 | 39 | -77 | 34,631 | POINT (-77.19406 38.86463) | 616,000 | Virginia | Aerospace & Defense | Northrop Grumman |
| 12 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | 616,000 | Virginia | Aerospace & Defense | General Dynamics |
| 13 | 22209 | 39 | -77 | 13,725 | POINT (-77.07309 38.89413) | 616,000 | Virginia | Aerospace & Defense | RTX |
| 14 | 22202 | 39 | -77 | 27,352 | POINT (-77.05175 38.8569) | 616,000 | Virginia | Aerospace & Defense | Boeing |
| 15 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | 607,300 | Michigan | Motor Vehicles & Parts | Autoliv |
| 16 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | 607,300 | Michigan | Motor Vehicles & Parts | BorgWarner |
| 17 | 48126 | 42 | -83 | 52,075 | POINT (-83.18678 42.32999) | 607,300 | Michigan | Motor Vehicles & Parts | Ford Motor |
| 18 | 48265 | 42 | -83 | 4,503 | POINT (-83.0456 42.3317) | 607,300 | Michigan | Motor Vehicles & Parts | General Motors |
| 19 | 48033 | 42 | -83 | 16,900 | POINT (-83.28812 42.46478) | 607,300 | Michigan | Motor Vehicles & Parts | Lear |
| 20 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | 470,100 | Georgia | Specialty Retailers: Other | Home Depot |
| 21 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | 450,000 | California | Information Technology Services | Concentrix |
| 22 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | 440,000 | Minnesota | General Merchandisers | Target |
| 23 | 38120 | 35 | -90 | 13,249 | POINT (-89.85237 35.12344) | 422,100 | Tennessee | Mail, Package and Freight Delivery | FedEx |
| 24 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | 409,000 | Ohio | Food & Drug Stores | Kroger |
| 25 | 68131 | 41 | -96 | 13,928 | POINT (-95.96479 41.26435) | 392,400 | Nebraska | Insurance: Property and Casualty (Stock) | Berkshire Hathaway |
| 26 | 01701 | 42 | -71 | 32,270 | POINT (-71.43796 42.32195) | 364,000 | Massachusetts | Specialty Retailers: Apparel | TJX |
| 27 | 07666 | 41 | -74 | 41,499 | POINT (-74.01067 40.88998) | 336,800 | New Jersey | Information Technology Services | Cognizant Technology |
| 28 | 28255 | 35 | -81 | 0 | POINT (-80.8434 35.2267) | 268,100 | North Carolina | Commercial Banks | Bank of America |
| 29 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | 268,100 | North Carolina | Commercial Banks | Truist Financial |
| 30 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | 268,100 | North Carolina | Commercial Banks | First Citizens BancShares |
| 31 | 19103 | 40 | -75 | 25,602 | POINT (-75.17386 39.95303) | 266,700 | Pennsylvania | Diversified Outsourcing Services | Aramark |
| 32 | 02895 | 42 | -71 | 43,081 | POINT (-71.49923 42.00103) | 259,500 | Rhode Island | Health Care: Pharmacy and Other Services | CVS Health |
| 33 | 33811 | 28 | -82 | 28,456 | POINT (-82.01866 27.97933) | 255,000 | Florida | Food & Drug Stores | Publix Super Markets |
| 34 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | 252,500 | Illinois | Food & Drug Stores | Walgreens |
| 35 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | 245,500 | Texas | Food Services | Yum China s |
| 36 | 83706 | 44 | -116 | 36,183 | POINT (-116.19427 43.59108) | 196,600 | Idaho | Food & Drug Stores | Albertsons |
| 37 | 06831 | 41 | -74 | 14,656 | POINT (-73.66078 41.08782) | 168,000 | Connecticut | Transportation and Logistics | GXO Logistics |
| 38 | 06831 | 41 | -74 | 14,656 | POINT (-73.66078 41.08782) | 168,000 | Connecticut | Transportation and Logistics | XPO |
| 39 | 89501 | 40 | -120 | 3,641 | POINT (-119.81262 39.52602) | 159,100 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment |
| 40 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | 159,100 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands |
| 41 | 89109 | 36 | -115 | 6,924 | POINT (-115.16327 36.12603) | 159,100 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International |
| 42 | 20814 | 39 | -77 | 30,822 | POINT (-77.10295 39.00506) | 155,000 | Maryland | Hotels, Casinos, Resorts | Marriott International |
| 43 | 46204 | 40 | -86 | 11,022 | POINT (-86.15703 39.77134) | 103,700 | Indiana | Health Care: Insurance and Managed Care | Elevance Health |
| 44 | 65802 | 37 | -93 | 46,005 | POINT (-93.35167 37.21048) | 85,600 | Missouri | Specialty Retailers: Other | O'Reilly Automotive |
| 45 | 97005 | 45 | -123 | 27,812 | POINT (-122.80397 45.49144) | 79,400 | Oregon | Apparel | Nike |
| 46 | 80202 | 40 | -105 | 18,233 | POINT (-104.99768 39.75156) | 76,000 | Colorado | Health Care: Medical Facilities | DaVita |
| 47 | 40202 | 38 | -86 | 7,109 | POINT (-85.75205 38.25288) | 65,700 | Kentucky | Health Care: Insurance and Managed Care | Humana |
| 48 | 20037 | 39 | -77 | 12,441 | POINT (-77.0535 38.89213) | 62,000 | District of Columbia | Medical Products and Equipment | Danaher |
| 49 | 53051 | 43 | -88 | 39,000 | POINT (-88.12348 43.14905) | 60,000 | Wisconsin | General Merchandisers | Kohl's |
| 50 | 85054 | 34 | -112 | 10,159 | POINT (-111.94763 33.67515) | 42,000 | Arizona | Waste Management | Republic Services |
| 51 | 50021 | 42 | -94 | 29,718 | POINT (-93.56838 41.7207) | 33,100 | Iowa | Specialty Retailers: Other | Casey's General Stores |
| 52 | 71203 | 33 | -92 | 38,770 | POINT (-92.01351 32.58398) | 25,000 | Louisiana | Telecommunications | Lumen Technologies |
| 53 | 19805 | 40 | -76 | 40,315 | POINT (-75.59373 39.74523) | 24,000 | Delaware | Chemicals | DuPont |
| 54 | 35203 | 34 | -87 | 3,301 | POINT (-86.80999 33.51847) | 19,600 | Alabama | Commercial Banks | Regions Financial |
| 55 | 66202 | 39 | -95 | 17,321 | POINT (-94.66909 39.02392) | 14,000 | Kansas | Food Production | Seaboard |
| 56 | 74103 | 36 | -96 | 2,419 | POINT (-95.9957 36.15617) | 11,000 | Oklahoma | Pipelines | Oneok |
| 57 | 74172 | 36 | -96 | 0 | POINT (-95.9905 36.1544) | 11,000 | Oklahoma | Pipelines | Williams |
In [106]:
mstmaxempin = gdfstsmaxempin.explore(column='Employees', name='The Biggest Employer Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactmaxempin.explore(m=mstmaxempin, column='Employees', name='The Biggest Employer Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxempin)
mstmaxempin
Out[106]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [107]:
# Check the Smallest Employer Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Employees': [1],
'State': ['Dummy'],
'Industry': ['Dummy']}
dfstminempin = pd.DataFrame(dummy)
for st in stslist[0:]:
dfst = df.where(df['State'] == st[0]).dropna()
dfstminempin = pd.concat([dfstminempin, dfst.groupby(['State','Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'],
ascending=True)[['State','Industry','Employees']].head(1)])
dfstminempin = dfstminempin.iloc[1:]
dfstminempin = dfstminempin.reset_index(drop=True)
dfstminempin[['State','Industry','Employees']].sort_values(by=['Employees'], ascending=False).reset_index(drop=True)
Out[107]:
| State | Industry | Employees | |
|---|---|---|---|
| 0 | Nevada | Hotels, Casinos, Resorts | 159,100 |
| 1 | Idaho | Semiconductors and Other Electronic Components | 48,000 |
| 2 | Kentucky | Food Services | 31,700 |
| 3 | Oregon | Automotive Retailing, Services | 30,200 |
| 4 | Delaware | Chemicals | 24,000 |
| 5 | Iowa | Insurance: Life, Health (Stock) | 19,700 |
| 6 | Washington | Transportation and Logistics | 18,900 |
| 7 | Illinois | Information Technology Services | 15,100 |
| 8 | Maryland | Energy | 14,200 |
| 9 | Kansas | Food Production | 14,000 |
| 10 | Colorado | Telecommunications | 13,700 |
| 11 | Indiana | Metals | 13,000 |
| 12 | Louisiana | Utilities: Gas and Electric | 12,300 |
| 13 | Alabama | Building Materials, Glass | 12,000 |
| 14 | Arkansas | Specialty Retailers: Other | 11,600 |
| 15 | North Carolina | Automotive Retailing, Services | 10,800 |
| 16 | District of Columbia | Diversified Financials | 8,200 |
| 17 | Michigan | Insurance: Property and Casualty (Mutual) | 7,300 |
| 18 | Wisconsin | Utilities: Gas and Electric | 7,000 |
| 19 | Georgia | Homebuilders | 6,800 |
| 20 | Nebraska | Insurance: Life, Health (Mutual) | 6,500 |
| 21 | Virginia | Tobacco | 6,200 |
| 22 | Rhode Island | Insurance: Property and Casualty (Stock) | 5,800 |
| 23 | Texas | Diversified Financials | 5,200 |
| 24 | Pennsylvania | Homebuilders | 4,900 |
| 25 | Florida | Energy | 4,700 |
| 26 | Massachusetts | Real Estate | 4,700 |
| 27 | Missouri | Insurance: Life, Health (Stock) | 4,100 |
| 28 | Minnesota | Insurance: Life, Health (Mutual) | 4,000 |
| 29 | New Jersey | Petroleum Refining | 3,900 |
| 30 | Connecticut | Securities | 3,000 |
| 31 | Arizona | Homebuilders | 3,000 |
| 32 | Oklahoma | Mining, Crude-Oil Production | 2,300 |
| 33 | Tennessee | Petroleum Refining | 2,000 |
| 34 | New York | Mining, Crude-Oil Production | 1,800 |
| 35 | Ohio | Real Estate | 700 |
| 36 | California | Wholesalers: Diversified | 500 |
In [108]:
dfstminempin = dfstminempin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstminempin[['State','Industry','Company','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[108]:
| State | Industry | Company | Zip Code | Employees | |
|---|---|---|---|---|---|
| 0 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment | 89501 | 159,100 |
| 1 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands | 89113 | 159,100 |
| 2 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International | 89109 | 159,100 |
| 3 | Idaho | Semiconductors and Other Electronic Components | Micron Technology | 83716 | 48,000 |
| 4 | Kentucky | Food Services | Yum Brands | 40213 | 31,700 |
| 5 | Oregon | Automotive Retailing, Services | Lithia Motors | 97501 | 30,200 |
| 6 | Delaware | Chemicals | DuPont | 19805 | 24,000 |
| 7 | Iowa | Insurance: Life, Health (Stock) | Principal Financial | 50392 | 19,700 |
| 8 | Washington | Transportation and Logistics | Expeditors International of Washington | 98006 | 18,900 |
| 9 | Illinois | Information Technology Services | CDW | 60061 | 15,100 |
| 10 | Maryland | Energy | Constellation Energy | 21231 | 14,200 |
| 11 | Kansas | Food Production | Seaboard | 66202 | 14,000 |
| 12 | Colorado | Telecommunications | EchoStar | 80112 | 13,700 |
| 13 | Indiana | Metals | Steel Dynamics | 46804 | 13,000 |
| 14 | Louisiana | Utilities: Gas and Electric | Entergy | 70113 | 12,300 |
| 15 | Alabama | Building Materials, Glass | Vulcan Materials | 35242 | 12,000 |
| 16 | Arkansas | Specialty Retailers: Other | Murphy USA | 71730 | 11,600 |
| 17 | North Carolina | Automotive Retailing, Services | Sonic Automotive | 28211 | 10,800 |
| 18 | District of Columbia | Diversified Financials | Fannie Mae | 20005 | 8,200 |
| 19 | Michigan | Insurance: Property and Casualty (Mutual) | Auto-Owners Insurance | 48917 | 7,300 |
| 20 | Wisconsin | Utilities: Gas and Electric | WEC Energy | 53203 | 7,000 |
| 21 | Georgia | Homebuilders | Pulte | 30326 | 6,800 |
| 22 | Nebraska | Insurance: Life, Health (Mutual) | Mutual of Omaha Insurance | 68175 | 6,500 |
| 23 | Virginia | Tobacco | Altria | 23230 | 6,200 |
| 24 | Rhode Island | Insurance: Property and Casualty (Stock) | FM | 02919 | 5,800 |
| 25 | Texas | Diversified Financials | Corebridge Financial | 77019 | 5,200 |
| 26 | Pennsylvania | Homebuilders | Toll Brothers | 19034 | 4,900 |
| 27 | Massachusetts | Real Estate | American Tower | 02116 | 4,700 |
| 28 | Florida | Energy | World Kinect | 33178 | 4,700 |
| 29 | Missouri | Insurance: Life, Health (Stock) | Reinsurance of America | 63017 | 4,100 |
| 30 | Minnesota | Insurance: Life, Health (Mutual) | Thrivent Financial for Lutherans | 55415 | 4,000 |
| 31 | New Jersey | Petroleum Refining | PBF Energy | 07054 | 3,900 |
| 32 | Connecticut | Securities | Interactive Brokers | 06830 | 3,000 |
| 33 | Arizona | Homebuilders | Taylor Morrison Home | 85251 | 3,000 |
| 34 | Oklahoma | Mining, Crude-Oil Production | Devon Energy | 73102 | 2,300 |
| 35 | Tennessee | Petroleum Refining | Delek US | 37027 | 2,000 |
| 36 | New York | Mining, Crude-Oil Production | Hess | 10036 | 1,800 |
| 37 | Ohio | Real Estate | Welltower | 43615 | 700 |
| 38 | California | Wholesalers: Diversified | A-Mark Precious Metals | 90245 | 500 |
In [109]:
gdfstsminempin = gdfsts.merge(dfstminempin, how = 'inner', on = ['State'])
gdfusactminempin = gdfusact.merge(dfstminempin, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactminempin
Out[109]:
| Zip Code | Latitude | Longitude | Population | geometry | Employees | State | Industry | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 89501 | 40 | -120 | 3,641 | POINT (-119.81262 39.52602) | 159,100 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment |
| 1 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | 159,100 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands |
| 2 | 89109 | 36 | -115 | 6,924 | POINT (-115.16327 36.12603) | 159,100 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International |
| 3 | 83716 | 44 | -116 | 21,091 | POINT (-115.6548 43.67271) | 48,000 | Idaho | Semiconductors and Other Electronic Components | Micron Technology |
| 4 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | 31,700 | Kentucky | Food Services | Yum Brands |
| 5 | 97501 | 42 | -123 | 45,008 | POINT (-122.89459 42.2856) | 30,200 | Oregon | Automotive Retailing, Services | Lithia Motors |
| 6 | 19805 | 40 | -76 | 40,315 | POINT (-75.59373 39.74523) | 24,000 | Delaware | Chemicals | DuPont |
| 7 | 50392 | 42 | -94 | 15,018 | POINT (-93.628 41.5898) | 19,700 | Iowa | Insurance: Life, Health (Stock) | Principal Financial |
| 8 | 98006 | 48 | -122 | 40,770 | POINT (-122.14957 47.55772) | 18,900 | Washington | Transportation and Logistics | Expeditors International of Washington |
| 9 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | 15,100 | Illinois | Information Technology Services | CDW |
| 10 | 21231 | 39 | -77 | 14,556 | POINT (-76.592 39.28775) | 14,200 | Maryland | Energy | Constellation Energy |
| 11 | 66202 | 39 | -95 | 17,321 | POINT (-94.66909 39.02392) | 14,000 | Kansas | Food Production | Seaboard |
| 12 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | 13,700 | Colorado | Telecommunications | EchoStar |
| 13 | 46804 | 41 | -85 | 29,177 | POINT (-85.23913 41.05421) | 13,000 | Indiana | Metals | Steel Dynamics |
| 14 | 70113 | 30 | -90 | 9,888 | POINT (-90.08382 29.9422) | 12,300 | Louisiana | Utilities: Gas and Electric | Entergy |
| 15 | 35242 | 33 | -87 | 56,956 | POINT (-86.67073 33.42371) | 12,000 | Alabama | Building Materials, Glass | Vulcan Materials |
| 16 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | 11,600 | Arkansas | Specialty Retailers: Other | Murphy USA |
| 17 | 28211 | 35 | -81 | 32,637 | POINT (-80.79604 35.16816) | 10,800 | North Carolina | Automotive Retailing, Services | Sonic Automotive |
| 18 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | 8,200 | District of Columbia | Diversified Financials | Fannie Mae |
| 19 | 48917 | 43 | -85 | 32,029 | POINT (-84.63897 42.72509) | 7,300 | Michigan | Insurance: Property and Casualty (Mutual) | Auto-Owners Insurance |
| 20 | 53203 | 43 | -88 | 2,077 | POINT (-87.91603 43.03828) | 7,000 | Wisconsin | Utilities: Gas and Electric | WEC Energy |
| 21 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | 6,800 | Georgia | Homebuilders | Pulte |
| 22 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | 6,500 | Nebraska | Insurance: Life, Health (Mutual) | Mutual of Omaha Insurance |
| 23 | 23230 | 38 | -77 | 8,304 | POINT (-77.49153 37.587) | 6,200 | Virginia | Tobacco | Altria |
| 24 | 02919 | 42 | -72 | 29,473 | POINT (-71.52002 41.82733) | 5,800 | Rhode Island | Insurance: Property and Casualty (Stock) | FM |
| 25 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | 5,200 | Texas | Diversified Financials | Corebridge Financial |
| 26 | 19034 | 40 | -75 | 7,084 | POINT (-75.20953 40.13353) | 4,900 | Pennsylvania | Homebuilders | Toll Brothers |
| 27 | 33178 | 26 | -80 | 65,515 | POINT (-80.4213 25.83578) | 4,700 | Florida | Energy | World Kinect |
| 28 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | 4,700 | Massachusetts | Real Estate | American Tower |
| 29 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | 4,100 | Missouri | Insurance: Life, Health (Stock) | Reinsurance of America |
| 30 | 55415 | 45 | -93 | 6,474 | POINT (-93.2578 44.97463) | 4,000 | Minnesota | Insurance: Life, Health (Mutual) | Thrivent Financial for Lutherans |
| 31 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | 3,900 | New Jersey | Petroleum Refining | PBF Energy |
| 32 | 85251 | 33 | -112 | 39,976 | POINT (-111.92025 33.49406) | 3,000 | Arizona | Homebuilders | Taylor Morrison Home |
| 33 | 06830 | 41 | -74 | 24,919 | POINT (-73.624 41.048) | 3,000 | Connecticut | Securities | Interactive Brokers |
| 34 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | 2,300 | Oklahoma | Mining, Crude-Oil Production | Devon Energy |
| 35 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | 2,000 | Tennessee | Petroleum Refining | Delek US |
| 36 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | 1,800 | New York | Mining, Crude-Oil Production | Hess |
| 37 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | 700 | Ohio | Real Estate | Welltower |
| 38 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | 500 | California | Wholesalers: Diversified | A-Mark Precious Metals |
In [110]:
mstminempin = gdfstsminempin.explore(column='Employees', name='The Smallest Employer Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactminempin.explore(m=mstminempin, column='Employees', name='The Smallest Employer Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstminempin)
mstminempin
Out[110]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [111]:
# Check the Biggest Revenue Industry in US (all States combined) (other viewpoint)
# a.k.a the Biggest Total Revenue Industry in US.
dfusmaxrevin = df.groupby(['Industry'], as_index=False).sum('Revenue (rounded)').sort_values(by=['Revenue (rounded)'], ascending=False)[['Industry','Revenue (rounded)']].reset_index(drop=True)
dfusmaxrevin10 = dfusmaxrevin.head(10)
dfusmaxrevin
Out[111]:
| Industry | Revenue (rounded) | |
|---|---|---|
| 0 | Internet Services and Retailing | 1,330,100,000,000 |
| 1 | Commercial Banks | 1,321,000,000,000 |
| 2 | General Merchandisers | 1,116,800,000,000 |
| 3 | Petroleum Refining | 1,044,500,000,000 |
| 4 | Health Care: Insurance and Managed Care | 908,000,000,000 |
| 5 | Wholesalers: Health Care | 853,200,000,000 |
| 6 | Insurance: Property and Casualty (Stock) | 842,900,000,000 |
| 7 | Health Care: Pharmacy and Other Services | 669,500,000,000 |
| 8 | Diversified Financials | 627,600,000,000 |
| 9 | Computers, Office Equipment | 598,300,000,000 |
| 10 | Motor Vehicles & Parts | 590,800,000,000 |
| 11 | Specialty Retailers: Other | 505,200,000,000 |
| 12 | Pharmaceuticals | 487,300,000,000 |
| 13 | Telecommunications | 473,800,000,000 |
| 14 | Semiconductors and Other Electronic Components | 446,900,000,000 |
| 15 | Food & Drug Stores | 441,900,000,000 |
| 16 | Aerospace & Defense | 407,400,000,000 |
| 17 | Computer Software | 393,200,000,000 |
| 18 | Utilities: Gas and Electric | 329,200,000,000 |
| 19 | Insurance: Life, Health (Stock) | 299,200,000,000 |
| 20 | Pipelines | 268,400,000,000 |
| 21 | Food Consumer Products | 263,800,000,000 |
| 22 | Entertainment | 259,900,000,000 |
| 23 | Insurance: Life, Health (Mutual) | 249,800,000,000 |
| 24 | Insurance: Property and Casualty (Mutual) | 226,100,000,000 |
| 25 | Food Production | 222,800,000,000 |
| 26 | Airlines | 221,400,000,000 |
| 27 | Automotive Retailing, Services | 215,700,000,000 |
| 28 | Wholesalers: Food and Grocery | 211,900,000,000 |
| 29 | Mining, Crude-Oil Production | 210,700,000,000 |
| 30 | Industrial Machinery | 207,800,000,000 |
| 31 | Chemicals | 203,000,000,000 |
| 32 | Information Technology Services | 201,900,000,000 |
| 33 | Medical Products and Equipment | 184,600,000,000 |
| 34 | Mail, Package and Freight Delivery | 178,800,000,000 |
| 35 | Securities | 175,900,000,000 |
| 36 | Financial Data Services | 175,300,000,000 |
| 37 | Wholesalers: Diversified | 169,600,000,000 |
| 38 | Energy | 163,200,000,000 |
| 39 | Wholesalers: Electronics and Office Equipment | 158,200,000,000 |
| 40 | Household and Personal Products | 155,300,000,000 |
| 41 | Construction and Farm Machinery | 138,900,000,000 |
| 42 | Health Care: Medical Facilities | 132,500,000,000 |
| 43 | Specialty Retailers: Apparel | 121,800,000,000 |
| 44 | Homebuilders | 119,800,000,000 |
| 45 | Metals | 116,600,000,000 |
| 46 | Food Services | 103,600,000,000 |
| 47 | Engineering & Construction | 100,000,000,000 |
| 48 | Real Estate | 95,100,000,000 |
| 49 | Beverages | 91,600,000,000 |
| 50 | Diversified Outsourcing Services | 89,500,000,000 |
| 51 | Network and Other Communications Equipment | 87,800,000,000 |
| 52 | Packaging, Containers | 80,800,000,000 |
| 53 | Apparel | 79,600,000,000 |
| 54 | Hotels, Casinos, Resorts | 76,100,000,000 |
| 55 | Transportation and Logistics | 60,700,000,000 |
| 56 | Oil and Gas Equipment, Services | 59,600,000,000 |
| 57 | Tobacco | 58,300,000,000 |
| 58 | Railroads | 50,800,000,000 |
| 59 | Electronics, Electrical Equip. | 46,000,000,000 |
| 60 | Scientific, Photographic and Control Equipment | 42,900,000,000 |
| 61 | Waste Management | 38,100,000,000 |
| 62 | Building Materials, Glass | 34,800,000,000 |
| 63 | Advertising, Marketing | 26,400,000,000 |
| 64 | Home Equipment, Furnishings | 26,200,000,000 |
| 65 | Trucking, Truck Leasing | 12,100,000,000 |
| 66 | Publishing, Printing | 10,100,000,000 |
In [ ]:
# Conclusion: the Biggest Revenue Industry in US is 'Internet Services and Retailing'.
In [112]:
dfusmaxrevin10 = dfusmaxrevin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxrevin10[['Industry','Company','State','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[112]:
| Industry | Company | State | Zip Code | Revenue (rounded) | |
|---|---|---|---|---|---|
| 0 | Internet Services and Retailing | Amazon | Washington | 98109 | 1,330,100,000,000 |
| 1 | Internet Services and Retailing | Chewy | Florida | 33322 | 1,330,100,000,000 |
| 2 | Internet Services and Retailing | Alphabet | California | 94043 | 1,330,100,000,000 |
| 3 | Internet Services and Retailing | QVC | Colorado | 80112 | 1,330,100,000,000 |
| 4 | Internet Services and Retailing | DoorDash | California | 94107 | 1,330,100,000,000 |
| 5 | Internet Services and Retailing | Airbnb | California | 94103 | 1,330,100,000,000 |
| 6 | Internet Services and Retailing | Wayfair | Massachusetts | 02116 | 1,330,100,000,000 |
| 7 | Internet Services and Retailing | Ebay | California | 95125 | 1,330,100,000,000 |
| 8 | Internet Services and Retailing | Expedia | Washington | 98119 | 1,330,100,000,000 |
| 9 | Internet Services and Retailing | Booking s | Connecticut | 06854 | 1,330,100,000,000 |
| 10 | Internet Services and Retailing | Coupang | Washington | 98101 | 1,330,100,000,000 |
| 11 | Internet Services and Retailing | Uber | California | 94158 | 1,330,100,000,000 |
| 12 | Internet Services and Retailing | Meta | California | 94025 | 1,330,100,000,000 |
| 13 | Commercial Banks | Truist Financial | North Carolina | 28202 | 1,321,000,000,000 |
| 14 | Commercial Banks | KeyCorp | Ohio | 44114 | 1,321,000,000,000 |
| 15 | Commercial Banks | Regions Financial | Alabama | 35203 | 1,321,000,000,000 |
| 16 | Commercial Banks | Huntington Bancshares | Ohio | 43287 | 1,321,000,000,000 |
| 17 | Commercial Banks | Citizens Financial | Rhode Island | 02903 | 1,321,000,000,000 |
| 18 | Commercial Banks | Fifth Third Bancorp | Ohio | 45263 | 1,321,000,000,000 |
| 19 | Commercial Banks | M&T Bank | New York | 14203 | 1,321,000,000,000 |
| 20 | Commercial Banks | First Citizens BancShares | North Carolina | 27609 | 1,321,000,000,000 |
| 21 | Commercial Banks | State Street | Massachusetts | 02114 | 1,321,000,000,000 |
| 22 | Commercial Banks | Northern Trust | Illinois | 60603 | 1,321,000,000,000 |
| 23 | Commercial Banks | PNC | Pennsylvania | 15222 | 1,321,000,000,000 |
| 24 | Commercial Banks | U.S. Bancorp | Minnesota | 55402 | 1,321,000,000,000 |
| 25 | Commercial Banks | Capital One | Virginia | 22102 | 1,321,000,000,000 |
| 26 | Commercial Banks | Morgan Stanley | New York | 10036 | 1,321,000,000,000 |
| 27 | Commercial Banks | Wells Fargo | California | 94104 | 1,321,000,000,000 |
| 28 | Commercial Banks | Goldman Sachs | New York | 10282 | 1,321,000,000,000 |
| 29 | Commercial Banks | Citi | New York | 10013 | 1,321,000,000,000 |
| 30 | Commercial Banks | Bank of America | North Carolina | 28255 | 1,321,000,000,000 |
| 31 | Commercial Banks | JPMorgan Chase | New York | 10017 | 1,321,000,000,000 |
| 32 | Commercial Banks | Bank of New York | New York | 10286 | 1,321,000,000,000 |
| 33 | General Merchandisers | Macy's | New York | 10001 | 1,116,800,000,000 |
| 34 | General Merchandisers | Nordstrom | Washington | 98101 | 1,116,800,000,000 |
| 35 | General Merchandisers | Kohl's | Wisconsin | 53051 | 1,116,800,000,000 |
| 36 | General Merchandisers | BJ's Wholesale Club | Massachusetts | 01752 | 1,116,800,000,000 |
| 37 | General Merchandisers | Target | Minnesota | 55403 | 1,116,800,000,000 |
| 38 | General Merchandisers | Costco | Washington | 98027 | 1,116,800,000,000 |
| 39 | General Merchandisers | Walmart | Arkansas | 72712 | 1,116,800,000,000 |
| 40 | Petroleum Refining | Exxon Mobil | Texas | 77389 | 1,044,500,000,000 |
| 41 | Petroleum Refining | Chevron | Texas | 77002 | 1,044,500,000,000 |
| 42 | Petroleum Refining | Phillips 66 | Texas | 77042 | 1,044,500,000,000 |
| 43 | Petroleum Refining | Marathon Petroleum | Ohio | 45840 | 1,044,500,000,000 |
| 44 | Petroleum Refining | Valero Energy | Texas | 78249 | 1,044,500,000,000 |
| 45 | Petroleum Refining | PBF Energy | New Jersey | 07054 | 1,044,500,000,000 |
| 46 | Petroleum Refining | HF Sinclair | Texas | 75219 | 1,044,500,000,000 |
| 47 | Petroleum Refining | Delek US | Tennessee | 37027 | 1,044,500,000,000 |
| 48 | Petroleum Refining | Par Pacific | Texas | 77024 | 1,044,500,000,000 |
| 49 | Health Care: Insurance and Managed Care | Oscar Health | New York | 10013 | 908,000,000,000 |
| 50 | Health Care: Insurance and Managed Care | Molina Healthcare | California | 90802 | 908,000,000,000 |
| 51 | Health Care: Insurance and Managed Care | Humana | Kentucky | 40202 | 908,000,000,000 |
| 52 | Health Care: Insurance and Managed Care | Centene | Missouri | 63105 | 908,000,000,000 |
| 53 | Health Care: Insurance and Managed Care | UnitedHealth | Minnesota | 55344 | 908,000,000,000 |
| 54 | Health Care: Insurance and Managed Care | Elevance Health | Indiana | 46204 | 908,000,000,000 |
| 55 | Wholesalers: Health Care | McKesson | Texas | 75039 | 853,200,000,000 |
| 56 | Wholesalers: Health Care | Cencora | Pennsylvania | 19428 | 853,200,000,000 |
| 57 | Wholesalers: Health Care | Cardinal Health | Ohio | 43017 | 853,200,000,000 |
| 58 | Wholesalers: Health Care | Henry Schein | New York | 11747 | 853,200,000,000 |
| 59 | Wholesalers: Health Care | Owens & Minor | Virginia | 23060 | 853,200,000,000 |
| 60 | Insurance: Property and Casualty (Stock) | Loews | New York | 10019 | 842,900,000,000 |
| 61 | Insurance: Property and Casualty (Stock) | Old Republic International | Illinois | 60601 | 842,900,000,000 |
| 62 | Insurance: Property and Casualty (Stock) | American Financial | Ohio | 45202 | 842,900,000,000 |
| 63 | Insurance: Property and Casualty (Stock) | FM | Rhode Island | 02919 | 842,900,000,000 |
| 64 | Insurance: Property and Casualty (Stock) | Cincinnati Financial | Ohio | 45014 | 842,900,000,000 |
| 65 | Insurance: Property and Casualty (Stock) | Assurant | Georgia | 30339 | 842,900,000,000 |
| 66 | Insurance: Property and Casualty (Stock) | W.R. Berkley | Connecticut | 06830 | 842,900,000,000 |
| 67 | Insurance: Property and Casualty (Stock) | Fidelity National Financial | Florida | 32204 | 842,900,000,000 |
| 68 | Insurance: Property and Casualty (Stock) | Markel | Virginia | 23060 | 842,900,000,000 |
| 69 | Insurance: Property and Casualty (Stock) | American International | New York | 10020 | 842,900,000,000 |
| 70 | Insurance: Property and Casualty (Stock) | American Family Insurance | Wisconsin | 53783 | 842,900,000,000 |
| 71 | Insurance: Property and Casualty (Stock) | Hartford Insurance | Connecticut | 06155 | 842,900,000,000 |
| 72 | Insurance: Property and Casualty (Stock) | Travelers | New York | 10017 | 842,900,000,000 |
| 73 | Insurance: Property and Casualty (Stock) | USAA | Texas | 78288 | 842,900,000,000 |
| 74 | Insurance: Property and Casualty (Stock) | Liberty Mutual Insurance | Massachusetts | 02116 | 842,900,000,000 |
| 75 | Insurance: Property and Casualty (Stock) | Allstate | Illinois | 60062 | 842,900,000,000 |
| 76 | Insurance: Property and Casualty (Stock) | Progressive | Ohio | 44143 | 842,900,000,000 |
| 77 | Insurance: Property and Casualty (Stock) | Berkshire Hathaway | Nebraska | 68131 | 842,900,000,000 |
| 78 | Health Care: Pharmacy and Other Services | Labcorp s | North Carolina | 27215 | 669,500,000,000 |
| 79 | Health Care: Pharmacy and Other Services | Quest Diagnostics | New Jersey | 07094 | 669,500,000,000 |
| 80 | Health Care: Pharmacy and Other Services | BrightSpring Health Services | Kentucky | 40222 | 669,500,000,000 |
| 81 | Health Care: Pharmacy and Other Services | CVS Health | Rhode Island | 02895 | 669,500,000,000 |
| 82 | Health Care: Pharmacy and Other Services | IQVIA s | North Carolina | 27703 | 669,500,000,000 |
| 83 | Health Care: Pharmacy and Other Services | Cigna | Connecticut | 06002 | 669,500,000,000 |
| 84 | Diversified Financials | Corebridge Financial | Texas | 77019 | 627,600,000,000 |
| 85 | Diversified Financials | Voya Financial | New York | 10169 | 627,600,000,000 |
| 86 | Diversified Financials | Icahn Enterprises | Florida | 33160 | 627,600,000,000 |
| 87 | Diversified Financials | Jefferies Financial | New York | 10022 | 627,600,000,000 |
| 88 | Diversified Financials | Arthur J. Gallagher | Illinois | 60008 | 627,600,000,000 |
| 89 | Diversified Financials | Blackstone | New York | 10154 | 627,600,000,000 |
| 90 | Diversified Financials | Ameriprise Financial | Minnesota | 55474 | 627,600,000,000 |
| 91 | Diversified Financials | Ally Financial | Michigan | 48226 | 627,600,000,000 |
| 92 | Diversified Financials | Discover Financial | Illinois | 60015 | 627,600,000,000 |
| 93 | Diversified Financials | Synchrony Financial | Connecticut | 06902 | 627,600,000,000 |
| 94 | Diversified Financials | Marsh & McLennan | New York | 10036 | 627,600,000,000 |
| 95 | Diversified Financials | American Express | New York | 10285 | 627,600,000,000 |
| 96 | Diversified Financials | StoneX | New York | 10169 | 627,600,000,000 |
| 97 | Diversified Financials | Freddie Mac | Virginia | 22102 | 627,600,000,000 |
| 98 | Diversified Financials | Fannie Mae | District of Columbia | 20005 | 627,600,000,000 |
| 99 | Computers, Office Equipment | Apple | California | 95014 | 598,300,000,000 |
| 100 | Computers, Office Equipment | Dell Technologies | Texas | 78682 | 598,300,000,000 |
| 101 | Computers, Office Equipment | HP | California | 94304 | 598,300,000,000 |
| 102 | Computers, Office Equipment | Hewlett Packard | Texas | 77389 | 598,300,000,000 |
| 103 | Computers, Office Equipment | Super Micro Computer | California | 95131 | 598,300,000,000 |
| 104 | Computers, Office Equipment | Western Digital | California | 95119 | 598,300,000,000 |
In [113]:
gdfstsusmaxrevin10 = gdfsts.merge(dfusmaxrevin10, how = 'inner', on = ['State'])
gdfusactusmaxrevin10 = gdfusact.merge(dfusmaxrevin10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevin10
Out[113]:
| Zip Code | Latitude | Longitude | Population | geometry | Industry | Revenue (rounded) | State | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Internet Services and Retailing | 1,330,100,000,000 | Washington | Amazon |
| 1 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Internet Services and Retailing | 1,330,100,000,000 | Washington | Expedia |
| 2 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | Internet Services and Retailing | 1,330,100,000,000 | California | Airbnb |
| 3 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Internet Services and Retailing | 1,330,100,000,000 | Colorado | QVC |
| 4 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | Internet Services and Retailing | 1,330,100,000,000 | California | DoorDash |
| 5 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | Internet Services and Retailing | 1,330,100,000,000 | California | Uber |
| 6 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | Internet Services and Retailing | 1,330,100,000,000 | California | Ebay |
| 7 | 33322 | 26 | -80 | 40,522 | POINT (-80.27429 26.14997) | Internet Services and Retailing | 1,330,100,000,000 | Florida | Chewy |
| 8 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Internet Services and Retailing | 1,330,100,000,000 | Washington | Coupang |
| 9 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | Internet Services and Retailing | 1,330,100,000,000 | California | Meta |
| 10 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | Internet Services and Retailing | 1,330,100,000,000 | California | Alphabet |
| 11 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Internet Services and Retailing | 1,330,100,000,000 | Massachusetts | Wayfair |
| 12 | 06854 | 41 | -73 | 31,753 | POINT (-73.42972 41.09148) | Internet Services and Retailing | 1,330,100,000,000 | Connecticut | Booking s |
| 13 | 55402 | 45 | -93 | 760 | POINT (-93.27119 44.97608) | Commercial Banks | 1,321,000,000,000 | Minnesota | U.S. Bancorp |
| 14 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Commercial Banks | 1,321,000,000,000 | Rhode Island | Citizens Financial |
| 15 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | Commercial Banks | 1,321,000,000,000 | North Carolina | First Citizens BancShares |
| 16 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Commercial Banks | 1,321,000,000,000 | Illinois | Northern Trust |
| 17 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | Commercial Banks | 1,321,000,000,000 | California | Wells Fargo |
| 18 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | Commercial Banks | 1,321,000,000,000 | North Carolina | Truist Financial |
| 19 | 15222 | 40 | -80 | 5,649 | POINT (-79.9912 40.44998) | Commercial Banks | 1,321,000,000,000 | Pennsylvania | PNC |
| 20 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | Commercial Banks | 1,321,000,000,000 | New York | M&T Bank |
| 21 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | Commercial Banks | 1,321,000,000,000 | New York | Goldman Sachs |
| 22 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Commercial Banks | 1,321,000,000,000 | Ohio | Fifth Third Bancorp |
| 23 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Commercial Banks | 1,321,000,000,000 | Ohio | Huntington Bancshares |
| 24 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | Commercial Banks | 1,321,000,000,000 | New York | Morgan Stanley |
| 25 | 28255 | 35 | -81 | 0 | POINT (-80.8434 35.2267) | Commercial Banks | 1,321,000,000,000 | North Carolina | Bank of America |
| 26 | 35203 | 34 | -87 | 3,301 | POINT (-86.80999 33.51847) | Commercial Banks | 1,321,000,000,000 | Alabama | Regions Financial |
| 27 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | Commercial Banks | 1,321,000,000,000 | New York | Bank of New York |
| 28 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | Commercial Banks | 1,321,000,000,000 | New York | JPMorgan Chase |
| 29 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Commercial Banks | 1,321,000,000,000 | Ohio | KeyCorp |
| 30 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | Commercial Banks | 1,321,000,000,000 | New York | Citi |
| 31 | 02114 | 42 | -71 | 13,853 | POINT (-71.06686 42.36337) | Commercial Banks | 1,321,000,000,000 | Massachusetts | State Street |
| 32 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Commercial Banks | 1,321,000,000,000 | Virginia | Capital One |
| 33 | 53051 | 43 | -88 | 39,000 | POINT (-88.12348 43.14905) | General Merchandisers | 1,116,800,000,000 | Wisconsin | Kohl's |
| 34 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | General Merchandisers | 1,116,800,000,000 | Minnesota | Target |
| 35 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | General Merchandisers | 1,116,800,000,000 | Arkansas | Walmart |
| 36 | 01752 | 42 | -72 | 41,398 | POINT (-71.54681 42.3494) | General Merchandisers | 1,116,800,000,000 | Massachusetts | BJ's Wholesale Club |
| 37 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | General Merchandisers | 1,116,800,000,000 | Washington | Costco |
| 38 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | General Merchandisers | 1,116,800,000,000 | Washington | Nordstrom |
| 39 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | General Merchandisers | 1,116,800,000,000 | New York | Macy's |
| 40 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Petroleum Refining | 1,044,500,000,000 | Texas | Par Pacific |
| 41 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Petroleum Refining | 1,044,500,000,000 | Texas | Chevron |
| 42 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | Petroleum Refining | 1,044,500,000,000 | New Jersey | PBF Energy |
| 43 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Petroleum Refining | 1,044,500,000,000 | Texas | Valero Energy |
| 44 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Petroleum Refining | 1,044,500,000,000 | Texas | Exxon Mobil |
| 45 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | Petroleum Refining | 1,044,500,000,000 | Tennessee | Delek US |
| 46 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Petroleum Refining | 1,044,500,000,000 | Texas | HF Sinclair |
| 47 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Petroleum Refining | 1,044,500,000,000 | Texas | Phillips 66 |
| 48 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Petroleum Refining | 1,044,500,000,000 | Ohio | Marathon Petroleum |
| 49 | 55344 | 45 | -93 | 14,180 | POINT (-93.43037 44.86452) | Health Care: Insurance and Managed Care | 908,000,000,000 | Minnesota | UnitedHealth |
| 50 | 46204 | 40 | -86 | 11,022 | POINT (-86.15703 39.77134) | Health Care: Insurance and Managed Care | 908,000,000,000 | Indiana | Elevance Health |
| 51 | 63105 | 39 | -90 | 18,860 | POINT (-90.32812 38.64427) | Health Care: Insurance and Managed Care | 908,000,000,000 | Missouri | Centene |
| 52 | 90802 | 34 | -118 | 39,859 | POINT (-118.21143 33.75035) | Health Care: Insurance and Managed Care | 908,000,000,000 | California | Molina Healthcare |
| 53 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | Health Care: Insurance and Managed Care | 908,000,000,000 | New York | Oscar Health |
| 54 | 40202 | 38 | -86 | 7,109 | POINT (-85.75205 38.25288) | Health Care: Insurance and Managed Care | 908,000,000,000 | Kentucky | Humana |
| 55 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Wholesalers: Health Care | 853,200,000,000 | Ohio | Cardinal Health |
| 56 | 11747 | 41 | -73 | 19,826 | POINT (-73.40931 40.78372) | Wholesalers: Health Care | 853,200,000,000 | New York | Henry Schein |
| 57 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Wholesalers: Health Care | 853,200,000,000 | Pennsylvania | Cencora |
| 58 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Wholesalers: Health Care | 853,200,000,000 | Texas | McKesson |
| 59 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Wholesalers: Health Care | 853,200,000,000 | Virginia | Owens & Minor |
| 60 | 06155 | 42 | -73 | 121,054 | POINT (-72.6859 41.7638) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Connecticut | Hartford Insurance |
| 61 | 53783 | 43 | -89 | 0 | POINT (-89.4012 43.0731) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Wisconsin | American Family Insurance |
| 62 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Texas | USAA |
| 63 | 68131 | 41 | -96 | 13,928 | POINT (-95.96479 41.26435) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Nebraska | Berkshire Hathaway |
| 64 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Ohio | American Financial |
| 65 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Illinois | Old Republic International |
| 66 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Massachusetts | Liberty Mutual Insurance |
| 67 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | New York | Travelers |
| 68 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | New York | Loews |
| 69 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | New York | American International |
| 70 | 02919 | 42 | -72 | 29,473 | POINT (-71.52002 41.82733) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Rhode Island | FM |
| 71 | 60062 | 42 | -88 | 41,667 | POINT (-87.84235 42.12663) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Illinois | Allstate |
| 72 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Virginia | Markel |
| 73 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Georgia | Assurant |
| 74 | 32204 | 30 | -82 | 8,421 | POINT (-81.68095 30.31636) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Florida | Fidelity National Financial |
| 75 | 06830 | 41 | -74 | 24,919 | POINT (-73.624 41.048) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Connecticut | W.R. Berkley |
| 76 | 44143 | 42 | -81 | 24,337 | POINT (-81.47513 41.55358) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Ohio | Progressive |
| 77 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | Insurance: Property and Casualty (Stock) | 842,900,000,000 | Ohio | Cincinnati Financial |
| 78 | 02895 | 42 | -71 | 43,081 | POINT (-71.49923 42.00103) | Health Care: Pharmacy and Other Services | 669,500,000,000 | Rhode Island | CVS Health |
| 79 | 27703 | 36 | -79 | 62,994 | POINT (-78.80452 35.96299) | Health Care: Pharmacy and Other Services | 669,500,000,000 | North Carolina | IQVIA s |
| 80 | 27215 | 36 | -79 | 45,967 | POINT (-79.48729 36.03055) | Health Care: Pharmacy and Other Services | 669,500,000,000 | North Carolina | Labcorp s |
| 81 | 06002 | 42 | -73 | 21,547 | POINT (-72.73714 41.84286) | Health Care: Pharmacy and Other Services | 669,500,000,000 | Connecticut | Cigna |
| 82 | 07094 | 41 | -74 | 21,437 | POINT (-74.06588 40.78109) | Health Care: Pharmacy and Other Services | 669,500,000,000 | New Jersey | Quest Diagnostics |
| 83 | 40222 | 38 | -86 | 21,634 | POINT (-85.61173 38.26436) | Health Care: Pharmacy and Other Services | 669,500,000,000 | Kentucky | BrightSpring Health Services |
| 84 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | Diversified Financials | 627,600,000,000 | New York | Jefferies Financial |
| 85 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Diversified Financials | 627,600,000,000 | Connecticut | Synchrony Financial |
| 86 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | Diversified Financials | 627,600,000,000 | New York | American Express |
| 87 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Diversified Financials | 627,600,000,000 | Illinois | Discover Financial |
| 88 | 60008 | 42 | -88 | 22,949 | POINT (-88.0229 42.0739) | Diversified Financials | 627,600,000,000 | Illinois | Arthur J. Gallagher |
| 89 | 48226 | 42 | -83 | 6,893 | POINT (-83.05034 42.33182) | Diversified Financials | 627,600,000,000 | Michigan | Ally Financial |
| 90 | 33160 | 26 | -80 | 43,225 | POINT (-80.13583 25.93234) | Diversified Financials | 627,600,000,000 | Florida | Icahn Enterprises |
| 91 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | Diversified Financials | 627,600,000,000 | New York | Marsh & McLennan |
| 92 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | Diversified Financials | 627,600,000,000 | New York | Blackstone |
| 93 | 55474 | 45 | -93 | 28,071 | POINT (-93.27 44.98) | Diversified Financials | 627,600,000,000 | Minnesota | Ameriprise Financial |
| 94 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Diversified Financials | 627,600,000,000 | Texas | Corebridge Financial |
| 95 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | Diversified Financials | 627,600,000,000 | New York | StoneX |
| 96 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | Diversified Financials | 627,600,000,000 | New York | Voya Financial |
| 97 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Diversified Financials | 627,600,000,000 | Virginia | Freddie Mac |
| 98 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | Diversified Financials | 627,600,000,000 | District of Columbia | Fannie Mae |
| 99 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | Computers, Office Equipment | 598,300,000,000 | California | HP |
| 100 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | Computers, Office Equipment | 598,300,000,000 | California | Super Micro Computer |
| 101 | 95119 | 37 | -122 | 10,449 | POINT (-121.79077 37.22756) | Computers, Office Equipment | 598,300,000,000 | California | Western Digital |
| 102 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | Computers, Office Equipment | 598,300,000,000 | California | Apple |
| 103 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Computers, Office Equipment | 598,300,000,000 | Texas | Hewlett Packard |
| 104 | 78682 | 30 | -98 | 0 | POINT (-97.7273 30.4076) | Computers, Office Equipment | 598,300,000,000 | Texas | Dell Technologies |
In [114]:
musmaxrevin = gdfstsusmaxrevin10.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevin10.explore(m=musmaxrevin, column='Revenue (rounded)', name='The Biggest Revenue Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevin)
musmaxrevin
Out[114]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [ ]:
In [115]:
# Check the Biggest Employer Industry in US (all States combined)
dfusmaxempin = df.groupby(['Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'], ascending=False)[['Industry','Employees']].reset_index(drop=True)
dfusmaxempin10 = dfusmaxempin.head(10)
dfusmaxempin
Out[115]:
| Industry | Employees | |
|---|---|---|
| 0 | General Merchandisers | 3101200 |
| 1 | Internet Services and Retailing | 2071800 |
| 2 | Commercial Banks | 1577000 |
| 3 | Specialty Retailers: Other | 1558200 |
| 4 | Information Technology Services | 1478900 |
| 5 | Food & Drug Stores | 1148100 |
| 6 | Food Services | 1109800 |
| 7 | Aerospace & Defense | 911500 |
| 8 | Motor Vehicles & Parts | 893000 |
| 9 | Mail, Package and Freight Delivery | 794300 |
| 10 | Insurance: Property and Casualty (Stock) | 789100 |
| 11 | Specialty Retailers: Apparel | 669500 |
| 12 | Health Care: Insurance and Managed Care | 650300 |
| 13 | Semiconductors and Other Electronic Components | 627900 |
| 14 | Food Consumer Products | 604700 |
| 15 | Industrial Machinery | 594700 |
| 16 | Health Care: Medical Facilities | 573200 |
| 17 | Health Care: Pharmacy and Other Services | 572800 |
| 18 | Telecommunications | 566700 |
| 19 | Computer Software | 565200 |
| 20 | Diversified Outsourcing Services | 564900 |
| 21 | Pharmaceuticals | 549400 |
| 22 | Medical Products and Equipment | 501600 |
| 23 | Hotels, Casinos, Resorts | 495100 |
| 24 | Airlines | 467900 |
| 25 | Computers, Office Equipment | 447700 |
| 26 | Chemicals | 379700 |
| 27 | Diversified Financials | 350100 |
| 28 | Entertainment | 338000 |
| 29 | Utilities: Gas and Electric | 306200 |
| 30 | Real Estate | 273800 |
| 31 | Financial Data Services | 260100 |
| 32 | Wholesalers: Diversified | 255100 |
| 33 | Household and Personal Products | 255000 |
| 34 | Network and Other Communications Equipment | 251700 |
| 35 | Transportation and Logistics | 251400 |
| 36 | Food Production | 241400 |
| 37 | Engineering & Construction | 240500 |
| 38 | Automotive Retailing, Services | 232000 |
| 39 | Construction and Farm Machinery | 210900 |
| 40 | Packaging, Containers | 191400 |
| 41 | Wholesalers: Health Care | 188600 |
| 42 | Wholesalers: Food and Grocery | 186100 |
| 43 | Insurance: Life, Health (Stock) | 178200 |
| 44 | Securities | 172200 |
| 45 | Petroleum Refining | 160600 |
| 46 | Electronics, Electrical Equip. | 158300 |
| 47 | Metals | 140900 |
| 48 | Apparel | 140500 |
| 49 | Oil and Gas Equipment, Services | 139000 |
| 50 | Beverages | 131200 |
| 51 | Advertising, Marketing | 128200 |
| 52 | Scientific, Photographic and Control Equipment | 125000 |
| 53 | Energy | 121900 |
| 54 | Insurance: Property and Casualty (Mutual) | 113800 |
| 55 | Waste Management | 103700 |
| 56 | Tobacco | 89300 |
| 57 | Mining, Crude-Oil Production | 89000 |
| 58 | Wholesalers: Electronics and Office Equipment | 88900 |
| 59 | Home Equipment, Furnishings | 83600 |
| 60 | Railroads | 75500 |
| 61 | Insurance: Life, Health (Mutual) | 70800 |
| 62 | Building Materials, Glass | 66000 |
| 63 | Pipelines | 55200 |
| 64 | Homebuilders | 49800 |
| 65 | Trucking, Truck Leasing | 33600 |
| 66 | Publishing, Printing | 23900 |
In [ ]:
# Conclusion: the Biggest Employer Industry in US is General Merchandisers.
In [116]:
dfusmaxempin10 = dfusmaxempin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxempin10[['Industry','Company','State','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[116]:
| Industry | Company | State | Zip Code | Employees | |
|---|---|---|---|---|---|
| 0 | General Merchandisers | Walmart | Arkansas | 72712 | 3101200 |
| 1 | General Merchandisers | Target | Minnesota | 55403 | 3101200 |
| 2 | General Merchandisers | Macy's | New York | 10001 | 3101200 |
| 3 | General Merchandisers | BJ's Wholesale Club | Massachusetts | 01752 | 3101200 |
| 4 | General Merchandisers | Kohl's | Wisconsin | 53051 | 3101200 |
| 5 | General Merchandisers | Nordstrom | Washington | 98101 | 3101200 |
| 6 | General Merchandisers | Costco | Washington | 98027 | 3101200 |
| 7 | Internet Services and Retailing | Expedia | Washington | 98119 | 2071800 |
| 8 | Internet Services and Retailing | QVC | Colorado | 80112 | 2071800 |
| 9 | Internet Services and Retailing | Ebay | California | 95125 | 2071800 |
| 10 | Internet Services and Retailing | DoorDash | California | 94107 | 2071800 |
| 11 | Internet Services and Retailing | Airbnb | California | 94103 | 2071800 |
| 12 | Internet Services and Retailing | Chewy | Florida | 33322 | 2071800 |
| 13 | Internet Services and Retailing | Wayfair | Massachusetts | 02116 | 2071800 |
| 14 | Internet Services and Retailing | Booking s | Connecticut | 06854 | 2071800 |
| 15 | Internet Services and Retailing | Coupang | Washington | 98101 | 2071800 |
| 16 | Internet Services and Retailing | Uber | California | 94158 | 2071800 |
| 17 | Internet Services and Retailing | Meta | California | 94025 | 2071800 |
| 18 | Internet Services and Retailing | Alphabet | California | 94043 | 2071800 |
| 19 | Internet Services and Retailing | Amazon | Washington | 98109 | 2071800 |
| 20 | Commercial Banks | Truist Financial | North Carolina | 28202 | 1577000 |
| 21 | Commercial Banks | KeyCorp | Ohio | 44114 | 1577000 |
| 22 | Commercial Banks | Regions Financial | Alabama | 35203 | 1577000 |
| 23 | Commercial Banks | Huntington Bancshares | Ohio | 43287 | 1577000 |
| 24 | Commercial Banks | Citizens Financial | Rhode Island | 02903 | 1577000 |
| 25 | Commercial Banks | Fifth Third Bancorp | Ohio | 45263 | 1577000 |
| 26 | Commercial Banks | M&T Bank | New York | 14203 | 1577000 |
| 27 | Commercial Banks | First Citizens BancShares | North Carolina | 27609 | 1577000 |
| 28 | Commercial Banks | Northern Trust | Illinois | 60603 | 1577000 |
| 29 | Commercial Banks | State Street | Massachusetts | 02114 | 1577000 |
| 30 | Commercial Banks | Goldman Sachs | New York | 10282 | 1577000 |
| 31 | Commercial Banks | PNC | Pennsylvania | 15222 | 1577000 |
| 32 | Commercial Banks | Bank of New York | New York | 10286 | 1577000 |
| 33 | Commercial Banks | U.S. Bancorp | Minnesota | 55402 | 1577000 |
| 34 | Commercial Banks | Capital One | Virginia | 22102 | 1577000 |
| 35 | Commercial Banks | Morgan Stanley | New York | 10036 | 1577000 |
| 36 | Commercial Banks | Wells Fargo | California | 94104 | 1577000 |
| 37 | Commercial Banks | Citi | New York | 10013 | 1577000 |
| 38 | Commercial Banks | Bank of America | North Carolina | 28255 | 1577000 |
| 39 | Commercial Banks | JPMorgan Chase | New York | 10017 | 1577000 |
| 40 | Specialty Retailers: Other | United Rentals | Connecticut | 06902 | 1558200 |
| 41 | Specialty Retailers: Other | ARKO | Virginia | 23227 | 1558200 |
| 42 | Specialty Retailers: Other | Williams-Sonoma | California | 94109 | 1558200 |
| 43 | Specialty Retailers: Other | Advance Auto Parts | North Carolina | 27609 | 1558200 |
| 44 | Specialty Retailers: Other | Ulta Beauty | Illinois | 60440 | 1558200 |
| 45 | Specialty Retailers: Other | Casey's General Stores | Iowa | 50021 | 1558200 |
| 46 | Specialty Retailers: Other | Tractor Supply | Tennessee | 37027 | 1558200 |
| 47 | Specialty Retailers: Other | Dick's Sporting Goods | Pennsylvania | 15108 | 1558200 |
| 48 | Specialty Retailers: Other | O'Reilly Automotive | Missouri | 65802 | 1558200 |
| 49 | Specialty Retailers: Other | Best Buy | Minnesota | 55423 | 1558200 |
| 50 | Specialty Retailers: Other | Home Depot | Georgia | 30339 | 1558200 |
| 51 | Specialty Retailers: Other | Lowe's | North Carolina | 28117 | 1558200 |
| 52 | Specialty Retailers: Other | Murphy USA | Arkansas | 71730 | 1558200 |
| 53 | Specialty Retailers: Other | Dollar General | Tennessee | 37072 | 1558200 |
| 54 | Specialty Retailers: Other | AutoZone | Tennessee | 38103 | 1558200 |
| 55 | Specialty Retailers: Other | Dollar Tree | Virginia | 23320 | 1558200 |
| 56 | Information Technology Services | DXC Technology | Virginia | 20147 | 1478900 |
| 57 | Information Technology Services | Science Applications International | Virginia | 20190 | 1478900 |
| 58 | Information Technology Services | CACI International | Virginia | 20190 | 1478900 |
| 59 | Information Technology Services | KBR | Texas | 77002 | 1478900 |
| 60 | Information Technology Services | Concentrix | California | 94560 | 1478900 |
| 61 | Information Technology Services | Insight Enterprises | Arizona | 85286 | 1478900 |
| 62 | Information Technology Services | Kyndryl s | New York | 10017 | 1478900 |
| 63 | Information Technology Services | Leidos s | Virginia | 20190 | 1478900 |
| 64 | Information Technology Services | Cognizant Technology | New Jersey | 07666 | 1478900 |
| 65 | Information Technology Services | CDW | Illinois | 60061 | 1478900 |
| 66 | Information Technology Services | IBM | New York | 10504 | 1478900 |
| 67 | Information Technology Services | Booz Allen Hamilton | Virginia | 22102 | 1478900 |
| 68 | Food & Drug Stores | Walgreens | Illinois | 60015 | 1148100 |
| 69 | Food & Drug Stores | Kroger | Ohio | 45202 | 1148100 |
| 70 | Food & Drug Stores | Albertsons | Idaho | 83706 | 1148100 |
| 71 | Food & Drug Stores | Publix Super Markets | Florida | 33811 | 1148100 |
| 72 | Food & Drug Stores | Sprouts Farmers Market | Arizona | 85054 | 1148100 |
| 73 | Food Services | Chipotle Mexican Grill | California | 92660 | 1109800 |
| 74 | Food Services | Yum Brands | Kentucky | 40213 | 1109800 |
| 75 | Food Services | Yum China s | Texas | 75074 | 1109800 |
| 76 | Food Services | Darden Restaurants | Florida | 32837 | 1109800 |
| 77 | Food Services | McDonald's | Illinois | 60607 | 1109800 |
| 78 | Food Services | Starbucks | Washington | 98134 | 1109800 |
| 79 | Aerospace & Defense | General Electric | Ohio | 45215 | 911500 |
| 80 | Aerospace & Defense | TransDigm | Ohio | 44115 | 911500 |
| 81 | Aerospace & Defense | Huntington Ingalls Industries | Virginia | 23607 | 911500 |
| 82 | Aerospace & Defense | Textron | Rhode Island | 02903 | 911500 |
| 83 | Aerospace & Defense | L3Harris Technologies | Florida | 32919 | 911500 |
| 84 | Aerospace & Defense | Howmet Aerospace | Pennsylvania | 15212 | 911500 |
| 85 | Aerospace & Defense | Northrop Grumman | Virginia | 22042 | 911500 |
| 86 | Aerospace & Defense | Boeing | Virginia | 22202 | 911500 |
| 87 | Aerospace & Defense | Lockheed Martin | Maryland | 20817 | 911500 |
| 88 | Aerospace & Defense | RTX | Virginia | 22209 | 911500 |
| 89 | Aerospace & Defense | General Dynamics | Virginia | 20190 | 911500 |
| 90 | Motor Vehicles & Parts | Goodyear Tire & Rubber | Ohio | 44316 | 893000 |
| 91 | Motor Vehicles & Parts | THOR Industries | Indiana | 46514 | 893000 |
| 92 | Motor Vehicles & Parts | Dana | Ohio | 43537 | 893000 |
| 93 | Motor Vehicles & Parts | Autoliv | Michigan | 48326 | 893000 |
| 94 | Motor Vehicles & Parts | BorgWarner | Michigan | 48326 | 893000 |
| 95 | Motor Vehicles & Parts | Paccar | Washington | 98004 | 893000 |
| 96 | Motor Vehicles & Parts | Lear | Michigan | 48033 | 893000 |
| 97 | Motor Vehicles & Parts | Tesla | Texas | 78725 | 893000 |
| 98 | Motor Vehicles & Parts | Ford Motor | Michigan | 48126 | 893000 |
| 99 | Motor Vehicles & Parts | General Motors | Michigan | 48265 | 893000 |
| 100 | Mail, Package and Freight Delivery | UPS | Georgia | 30328 | 794300 |
| 101 | Mail, Package and Freight Delivery | FedEx | Tennessee | 38120 | 794300 |
In [117]:
gdfstsusmaxempin10 = gdfsts.merge(dfusmaxempin10, how = 'inner', on = ['State'])
gdfusactusmaxempin10 = gdfusact.merge(dfusmaxempin10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempin10
Out[117]:
| Zip Code | Latitude | Longitude | Population | geometry | Industry | Employees | State | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 01752 | 42 | -72 | 41,398 | POINT (-71.54681 42.3494) | General Merchandisers | 3101200 | Massachusetts | BJ's Wholesale Club |
| 1 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | General Merchandisers | 3101200 | Minnesota | Target |
| 2 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | General Merchandisers | 3101200 | Washington | Costco |
| 3 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | General Merchandisers | 3101200 | Arkansas | Walmart |
| 4 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | General Merchandisers | 3101200 | Washington | Nordstrom |
| 5 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | General Merchandisers | 3101200 | New York | Macy's |
| 6 | 53051 | 43 | -88 | 39,000 | POINT (-88.12348 43.14905) | General Merchandisers | 3101200 | Wisconsin | Kohl's |
| 7 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | Internet Services and Retailing | 2071800 | California | Airbnb |
| 8 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | Internet Services and Retailing | 2071800 | California | Alphabet |
| 9 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Internet Services and Retailing | 2071800 | Washington | Coupang |
| 10 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Internet Services and Retailing | 2071800 | Washington | Amazon |
| 11 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | Internet Services and Retailing | 2071800 | California | Meta |
| 12 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Internet Services and Retailing | 2071800 | Washington | Expedia |
| 13 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | Internet Services and Retailing | 2071800 | California | Uber |
| 14 | 33322 | 26 | -80 | 40,522 | POINT (-80.27429 26.14997) | Internet Services and Retailing | 2071800 | Florida | Chewy |
| 15 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | Internet Services and Retailing | 2071800 | California | Ebay |
| 16 | 02116 | 42 | -71 | 22,040 | POINT (-71.07638 42.35105) | Internet Services and Retailing | 2071800 | Massachusetts | Wayfair |
| 17 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Internet Services and Retailing | 2071800 | Colorado | QVC |
| 18 | 06854 | 41 | -73 | 31,753 | POINT (-73.42972 41.09148) | Internet Services and Retailing | 2071800 | Connecticut | Booking s |
| 19 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | Internet Services and Retailing | 2071800 | California | DoorDash |
| 20 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Commercial Banks | 1577000 | Ohio | KeyCorp |
| 21 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Commercial Banks | 1577000 | Illinois | Northern Trust |
| 22 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | Commercial Banks | 1577000 | California | Wells Fargo |
| 23 | 28202 | 35 | -81 | 16,855 | POINT (-80.8447 35.22773) | Commercial Banks | 1577000 | North Carolina | Truist Financial |
| 24 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Commercial Banks | 1577000 | Rhode Island | Citizens Financial |
| 25 | 02114 | 42 | -71 | 13,853 | POINT (-71.06686 42.36337) | Commercial Banks | 1577000 | Massachusetts | State Street |
| 26 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | Commercial Banks | 1577000 | North Carolina | First Citizens BancShares |
| 27 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Commercial Banks | 1577000 | Ohio | Fifth Third Bancorp |
| 28 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | Commercial Banks | 1577000 | New York | Citi |
| 29 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Commercial Banks | 1577000 | Ohio | Huntington Bancshares |
| 30 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | Commercial Banks | 1577000 | New York | JPMorgan Chase |
| 31 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Commercial Banks | 1577000 | Virginia | Capital One |
| 32 | 35203 | 34 | -87 | 3,301 | POINT (-86.80999 33.51847) | Commercial Banks | 1577000 | Alabama | Regions Financial |
| 33 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | Commercial Banks | 1577000 | New York | Bank of New York |
| 34 | 28255 | 35 | -81 | 0 | POINT (-80.8434 35.2267) | Commercial Banks | 1577000 | North Carolina | Bank of America |
| 35 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | Commercial Banks | 1577000 | New York | Morgan Stanley |
| 36 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | Commercial Banks | 1577000 | New York | Goldman Sachs |
| 37 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | Commercial Banks | 1577000 | New York | M&T Bank |
| 38 | 15222 | 40 | -80 | 5,649 | POINT (-79.9912 40.44998) | Commercial Banks | 1577000 | Pennsylvania | PNC |
| 39 | 55402 | 45 | -93 | 760 | POINT (-93.27119 44.97608) | Commercial Banks | 1577000 | Minnesota | U.S. Bancorp |
| 40 | 50021 | 42 | -94 | 29,718 | POINT (-93.56838 41.7207) | Specialty Retailers: Other | 1558200 | Iowa | Casey's General Stores |
| 41 | 55423 | 45 | -93 | 36,779 | POINT (-93.28144 44.87663) | Specialty Retailers: Other | 1558200 | Minnesota | Best Buy |
| 42 | 60440 | 42 | -88 | 52,074 | POINT (-88.07572 41.70125) | Specialty Retailers: Other | 1558200 | Illinois | Ulta Beauty |
| 43 | 65802 | 37 | -93 | 46,005 | POINT (-93.35167 37.21048) | Specialty Retailers: Other | 1558200 | Missouri | O'Reilly Automotive |
| 44 | 94109 | 38 | -122 | 54,397 | POINT (-122.42138 37.79334) | Specialty Retailers: Other | 1558200 | California | Williams-Sonoma |
| 45 | 28117 | 36 | -81 | 48,170 | POINT (-80.89658 35.57405) | Specialty Retailers: Other | 1558200 | North Carolina | Lowe's |
| 46 | 38103 | 35 | -90 | 14,025 | POINT (-90.05518 35.15308) | Specialty Retailers: Other | 1558200 | Tennessee | AutoZone |
| 47 | 23320 | 37 | -76 | 59,626 | POINT (-76.21807 36.75208) | Specialty Retailers: Other | 1558200 | Virginia | Dollar Tree |
| 48 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Specialty Retailers: Other | 1558200 | Connecticut | United Rentals |
| 49 | 15108 | 41 | -80 | 42,782 | POINT (-80.20031 40.50006) | Specialty Retailers: Other | 1558200 | Pennsylvania | Dick's Sporting Goods |
| 50 | 37072 | 36 | -87 | 32,344 | POINT (-86.74494 36.35686) | Specialty Retailers: Other | 1558200 | Tennessee | Dollar General |
| 51 | 23227 | 38 | -77 | 25,574 | POINT (-77.44234 37.61486) | Specialty Retailers: Other | 1558200 | Virginia | ARKO |
| 52 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | Specialty Retailers: Other | 1558200 | Arkansas | Murphy USA |
| 53 | 27609 | 36 | -79 | 35,548 | POINT (-78.63282 35.8437) | Specialty Retailers: Other | 1558200 | North Carolina | Advance Auto Parts |
| 54 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | Specialty Retailers: Other | 1558200 | Tennessee | Tractor Supply |
| 55 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Specialty Retailers: Other | 1558200 | Georgia | Home Depot |
| 56 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | Information Technology Services | 1478900 | California | Concentrix |
| 57 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Information Technology Services | 1478900 | Texas | KBR |
| 58 | 07666 | 41 | -74 | 41,499 | POINT (-74.01067 40.88998) | Information Technology Services | 1478900 | New Jersey | Cognizant Technology |
| 59 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | Information Technology Services | 1478900 | New York | Kyndryl s |
| 60 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | Information Technology Services | 1478900 | Illinois | CDW |
| 61 | 10504 | 41 | -74 | 7,853 | POINT (-73.70629 41.13065) | Information Technology Services | 1478900 | New York | IBM |
| 62 | 20147 | 39 | -77 | 67,007 | POINT (-77.47958 39.04151) | Information Technology Services | 1478900 | Virginia | DXC Technology |
| 63 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Information Technology Services | 1478900 | Virginia | Booz Allen Hamilton |
| 64 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Information Technology Services | 1478900 | Virginia | Leidos s |
| 65 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Information Technology Services | 1478900 | Virginia | CACI International |
| 66 | 85286 | 33 | -112 | 49,870 | POINT (-111.83156 33.27146) | Information Technology Services | 1478900 | Arizona | Insight Enterprises |
| 67 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Information Technology Services | 1478900 | Virginia | Science Applications International |
| 68 | 83706 | 44 | -116 | 36,183 | POINT (-116.19427 43.59108) | Food & Drug Stores | 1148100 | Idaho | Albertsons |
| 69 | 85054 | 34 | -112 | 10,159 | POINT (-111.94763 33.67515) | Food & Drug Stores | 1148100 | Arizona | Sprouts Farmers Market |
| 70 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Food & Drug Stores | 1148100 | Ohio | Kroger |
| 71 | 33811 | 28 | -82 | 28,456 | POINT (-82.01866 27.97933) | Food & Drug Stores | 1148100 | Florida | Publix Super Markets |
| 72 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Food & Drug Stores | 1148100 | Illinois | Walgreens |
| 73 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | Food Services | 1109800 | California | Chipotle Mexican Grill |
| 74 | 98134 | 48 | -122 | 779 | POINT (-122.33686 47.57691) | Food Services | 1109800 | Washington | Starbucks |
| 75 | 32837 | 28 | -81 | 49,889 | POINT (-81.41998 28.38074) | Food Services | 1109800 | Florida | Darden Restaurants |
| 76 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Food Services | 1109800 | Illinois | McDonald's |
| 77 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | Food Services | 1109800 | Kentucky | Yum Brands |
| 78 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | Food Services | 1109800 | Texas | Yum China s |
| 79 | 23607 | 37 | -76 | 23,028 | POINT (-76.42235 36.98753) | Aerospace & Defense | 911500 | Virginia | Huntington Ingalls Industries |
| 80 | 22202 | 39 | -77 | 27,352 | POINT (-77.05175 38.8569) | Aerospace & Defense | 911500 | Virginia | Boeing |
| 81 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | Aerospace & Defense | 911500 | Ohio | General Electric |
| 82 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Aerospace & Defense | 911500 | Ohio | TransDigm |
| 83 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Aerospace & Defense | 911500 | Rhode Island | Textron |
| 84 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Aerospace & Defense | 911500 | Pennsylvania | Howmet Aerospace |
| 85 | 32919 | 28 | -81 | 0 | POINT (-80.6386 28.0909) | Aerospace & Defense | 911500 | Florida | L3Harris Technologies |
| 86 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Aerospace & Defense | 911500 | Virginia | General Dynamics |
| 87 | 20817 | 39 | -77 | 37,738 | POINT (-77.14919 38.99809) | Aerospace & Defense | 911500 | Maryland | Lockheed Martin |
| 88 | 22042 | 39 | -77 | 34,631 | POINT (-77.19406 38.86463) | Aerospace & Defense | 911500 | Virginia | Northrop Grumman |
| 89 | 22209 | 39 | -77 | 13,725 | POINT (-77.07309 38.89413) | Aerospace & Defense | 911500 | Virginia | RTX |
| 90 | 44316 | 41 | -81 | 0 | POINT (-81.47083 41.07854) | Motor Vehicles & Parts | 893000 | Ohio | Goodyear Tire & Rubber |
| 91 | 78725 | 30 | -98 | 10,810 | POINT (-97.60859 30.23554) | Motor Vehicles & Parts | 893000 | Texas | Tesla |
| 92 | 48033 | 42 | -83 | 16,900 | POINT (-83.28812 42.46478) | Motor Vehicles & Parts | 893000 | Michigan | Lear |
| 93 | 46514 | 42 | -86 | 41,480 | POINT (-85.97547 41.72328) | Motor Vehicles & Parts | 893000 | Indiana | THOR Industries |
| 94 | 98004 | 48 | -122 | 39,435 | POINT (-122.20548 47.61865) | Motor Vehicles & Parts | 893000 | Washington | Paccar |
| 95 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | Motor Vehicles & Parts | 893000 | Michigan | Autoliv |
| 96 | 48326 | 43 | -83 | 24,488 | POINT (-83.2531 42.67536) | Motor Vehicles & Parts | 893000 | Michigan | BorgWarner |
| 97 | 48126 | 42 | -83 | 52,075 | POINT (-83.18678 42.32999) | Motor Vehicles & Parts | 893000 | Michigan | Ford Motor |
| 98 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Motor Vehicles & Parts | 893000 | Ohio | Dana |
| 99 | 48265 | 42 | -83 | 4,503 | POINT (-83.0456 42.3317) | Motor Vehicles & Parts | 893000 | Michigan | General Motors |
| 100 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Mail, Package and Freight Delivery | 794300 | Georgia | UPS |
| 101 | 38120 | 35 | -90 | 13,249 | POINT (-89.85237 35.12344) | Mail, Package and Freight Delivery | 794300 | Tennessee | FedEx |
In [118]:
musmaxempin10 = gdfstsusmaxempin10.explore(column='Employees', name='The Biggest Employer Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempin10.explore(m=musmaxempin10, column='Employees', name='The Biggest Employer Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempin10)
musmaxempin10
Out[118]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [119]:
# Check the Most Efficient Company in each Industry
dfinsmaxeffco = df.head(1)
dfinsmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new
for ins in inslist[0:]:
dfin = df.where(df['Industry'] == ins[0]).dropna()
dfin['Efficiency'] = dfin['Revenue (rounded)']/dfin['Employees']
dfinsmaxeffco = pd.concat([dfinsmaxeffco, dfin.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
dfinsmaxeffco = dfinsmaxeffco.drop(0)
dfinsmaxeffco[['Industry','State','City','Company','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[119]:
| Industry | State | City | Company | Zip Code | Efficiency | |
|---|---|---|---|---|---|---|
| 0 | Diversified Financials | New York | New York | StoneX | 10169 | 22,200,000 |
| 1 | Wholesalers: Diversified | California | El Segundo | A-Mark Precious Metals | 90245 | 19,400,000 |
| 2 | Petroleum Refining | Texas | San Antonio | Valero Energy | 78249 | 12,525,253 |
| 3 | Pipelines | Texas | Houston | Plains GP | 77002 | 11,928,571 |
| 4 | Real Estate | Ohio | Toledo | Welltower | 43615 | 11,428,571 |
| 5 | Energy | Florida | Miami | World Kinect | 33178 | 8,978,723 |
| 6 | Mining, Crude-Oil Production | Texas | Houston | EOG Resources | 77002 | 7,406,250 |
| 7 | Wholesalers: Health Care | Pennsylvania | Conshohocken | Cencora | 19428 | 6,681,818 |
| 8 | Securities | New York | New York | KKR | 10001 | 6,229,167 |
| 9 | Insurance: Life, Health (Stock) | Missouri | Chesterfield | Reinsurance of America | 63017 | 5,390,244 |
| 10 | Insurance: Life, Health (Mutual) | Ohio | Cincinnati | Western & Southern Financial | 45202 | 5,111,111 |
| 11 | Food Production | Ohio | Maumee | Andersons | 43537 | 4,913,043 |
| 12 | Health Care: Insurance and Managed Care | New York | New York | Oscar Health | 10013 | 3,833,333 |
| 13 | Semiconductors and Other Electronic Components | California | Santa Clara | Nvidia | 95051 | 3,625,000 |
| 14 | Health Care: Pharmacy and Other Services | Connecticut | Bloomfield | Cigna | 06002 | 3,412,983 |
| 15 | Tobacco | Virginia | Richmond | Altria | 23230 | 3,290,323 |
| 16 | Entertainment | California | Los Gatos | Netflix | 95032 | 2,785,714 |
| 17 | Homebuilders | Arizona | Scottsdale | Taylor Morrison Home | 85251 | 2,733,333 |
| 18 | Commercial Banks | New York | New York | Goldman Sachs | 10282 | 2,729,032 |
| 19 | Computers, Office Equipment | California | San Jose | Super Micro Computer | 95131 | 2,631,579 |
| 20 | Insurance: Property and Casualty (Mutual) | Ohio | Columbus | Nationwide | 43215 | 2,604,444 |
| 21 | Wholesalers: Electronics and Office Equipment | California | Fremont | TD Synnex | 94538 | 2,267,442 |
| 22 | Internet Services and Retailing | California | Menlo Park | Meta | 94025 | 2,219,973 |
| 23 | Financial Data Services | California | Oakland | Block | 94612 | 2,114,035 |
| 24 | Insurance: Property and Casualty (Stock) | Ohio | Fairfield | Cincinnati Financial | 45014 | 2,017,857 |
| 25 | Pharmaceuticals | Massachusetts | Boston | Vertex Pharmaceuticals | 02210 | 1,803,279 |
| 26 | Food Consumer Products | Minnesota | Arden Hills | Land O'Lakes | 55126 | 1,800,000 |
| 27 | Specialty Retailers: Other | Arkansas | El Dorado | Murphy USA | 71730 | 1,543,103 |
| 28 | Wholesalers: Food and Grocery | Virginia | Richmond | Performance Food | 23238 | 1,486,413 |
| 29 | Utilities: Gas and Electric | Florida | Juno Beach | NextEra Energy | 33408 | 1,476,190 |
| 30 | Information Technology Services | Illinois | Vernon Hills | CDW | 60061 | 1,390,728 |
| 31 | Telecommunications | New York | New York | Verizon | 10036 | 1,353,414 |
| 32 | Metals | Indiana | Fort Wayne | Steel Dynamics | 46804 | 1,346,154 |
| 33 | Automotive Retailing, Services | North Carolina | Charlotte | Sonic Automotive | 28211 | 1,314,815 |
| 34 | Transportation and Logistics | Minnesota | Eden Prairie | C.H. Robinson Worldwide | 55347 | 1,282,609 |
| 35 | Beverages | California | Corona | Monster Beverage | 92879 | 1,250,000 |
| 36 | Chemicals | Michigan | Midland | Dow | 48674 | 1,194,444 |
| 37 | Motor Vehicles & Parts | Michigan | Detroit | General Motors | 48265 | 1,156,790 |
| 38 | Computer Software | Washington | Redmond | Microsoft | 98052 | 1,075,000 |
| 39 | Construction and Farm Machinery | Illinois | Moline | Deere | 61265 | 931,532 |
| 40 | Household and Personal Products | Ohio | Cincinnati | Procter & Gamble | 45202 | 777,778 |
| 41 | General Merchandisers | Washington | Issaquah | Costco | 98027 | 764,264 |
| 42 | Packaging, Containers | Colorado | Westminster | Ball | 80021 | 756,250 |
| 43 | Railroads | Nebraska | Omaha | Union Pacific | 68179 | 746,914 |
| 44 | Aerospace & Defense | Ohio | Evendale | General Electric | 45215 | 730,189 |
| 45 | Diversified Outsourcing Services | Wisconsin | Milwaukee | Manpower | 53212 | 670,412 |
| 46 | Apparel | Oregon | Beaverton | Nike | 97005 | 647,355 |
| 47 | Building Materials, Glass | Alabama | Birmingham | Vulcan Materials | 35242 | 616,667 |
| 48 | Engineering & Construction | Texas | Irving | Fluor | 75039 | 605,948 |
| 49 | Airlines | Georgia | Atlanta | Delta Airlines | 30354 | 598,058 |
| 50 | Network and Other Communications Equipment | California | San Jose | Cisco Systems | 95134 | 595,133 |
| 51 | Food & Drug Stores | Illinois | Deerfield | Walgreens | 60015 | 584,950 |
| 52 | Medical Products and Equipment | California | Sunnyvale | Intuitive Surgical | 94086 | 538,462 |
| 53 | Industrial Machinery | Florida | Palm Beach Gardens | Carrier Global | 33418 | 516,667 |
| 54 | Oil and Gas Equipment, Services | Texas | Houston | Baker Hughes | 77079 | 487,719 |
| 55 | Home Equipment, Furnishings | Michigan | Livonia | Masco | 48152 | 433,333 |
| 56 | Publishing, Printing | New York | New York | News Corp. | 10036 | 422,594 |
| 57 | Waste Management | Arizona | Phoenix | Republic Services | 85054 | 380,952 |
| 58 | Electronics, Electrical Equip. | Michigan | Benton Harbor | Whirlpool | 49022 | 377,273 |
| 59 | Trucking, Truck Leasing | Arkansas | Lowell | J.B. Hunt Transport Services | 72745 | 360,119 |
| 60 | Scientific, Photographic and Control Equipment | Massachusetts | Waltham | Thermo Fisher Scientific | 02451 | 343,200 |
| 61 | Hotels, Casinos, Resorts | Nevada | Las Vegas | Las Vegas Sands | 89113 | 281,796 |
| 62 | Specialty Retailers: Apparel | Washington | Sumner | Lululemon athletica | 98390 | 271,795 |
| 63 | Health Care: Medical Facilities | Tennessee | Nashville | HCA Healthcare | 37203 | 260,517 |
| 64 | Mail, Package and Freight Delivery | Georgia | Atlanta | UPS | 30328 | 244,761 |
| 65 | Food Services | Kentucky | Louisville | Yum Brands | 40213 | 236,593 |
| 66 | Advertising, Marketing | New York | New York | Omnicom | 10017 | 209,613 |
In [120]:
gdfstsinsmaxeffco = gdfsts.merge(dfinsmaxeffco, how = 'inner', on = ['State'])
gdfusactinsmaxeffco = gdfusact.merge(dfinsmaxeffco, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactinsmaxeffco
Out[120]:
| Zip Code | Latitude | Longitude | Population | geometry | Efficiency | Company | Industry | City | State | Website | Employees | Revenue (rounded) | CEO | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | 22,200,000 | StoneX | Diversified Financials | New York | New York | stonex.com | 4,500 | 99,900,000,000 | Philip Smith |
| 1 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | 19,400,000 | A-Mark Precious Metals | Wholesalers: Diversified | El Segundo | California | amark.com | 500 | 9,700,000,000 | Gregory Roberts |
| 2 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | 12,525,253 | Valero Energy | Petroleum Refining | San Antonio | Texas | valero.com | 9,900 | 124,000,000,000 | Lane Riggs |
| 3 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | 11,928,571 | Plains GP | Pipelines | Houston | Texas | plains.com | 4,200 | 50,100,000,000 | Wilfred Chiang |
| 4 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | 11,428,571 | Welltower | Real Estate | Toledo | Ohio | welltower.com | 700 | 8,000,000,000 | Shankh Mitra |
| 5 | 33178 | 26 | -80 | 65,515 | POINT (-80.4213 25.83578) | 8,978,723 | World Kinect | Energy | Miami | Florida | world-kinect.com | 4,700 | 42,200,000,000 | Michael Kasbar |
| 6 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | 7,406,250 | EOG Resources | Mining, Crude-Oil Production | Houston | Texas | eogresources.com | 3,200 | 23,700,000,000 | Ezra Yacob |
| 7 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | 6,681,818 | Cencora | Wholesalers: Health Care | Conshohocken | Pennsylvania | cencora.com | 44,000 | 294,000,000,000 | Robert Mauch |
| 8 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | 6,229,167 | KKR | Securities | New York | New York | kkr.com | 4,800 | 29,900,000,000 | Joseph Bae |
| 9 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | 5,390,244 | Reinsurance of America | Insurance: Life, Health (Stock) | Chesterfield | Missouri | rgare.com | 4,100 | 22,100,000,000 | Tony Cheng |
| 10 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | 5,111,111 | Western & Southern Financial | Insurance: Life, Health (Mutual) | Cincinnati | Ohio | westernsouthern.com | 2,700 | 13,800,000,000 | John Barrett |
| 11 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | 4,913,043 | Andersons | Food Production | Maumee | Ohio | andersonsinc.com | 2,300 | 11,300,000,000 | William Krueger |
| 12 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | 3,833,333 | Oscar Health | Health Care: Insurance and Managed Care | New York | New York | hioscar.com | 2,400 | 9,200,000,000 | Mark Bertolini |
| 13 | 95051 | 37 | -122 | 61,345 | POINT (-121.98444 37.3483) | 3,625,000 | Nvidia | Semiconductors and Other Electronic Components | Santa Clara | California | nvidia.com | 36,000 | 130,500,000,000 | Jensen Huang |
| 14 | 06002 | 42 | -73 | 21,547 | POINT (-72.73714 41.84286) | 3,412,983 | Cigna | Health Care: Pharmacy and Other Services | Bloomfield | Connecticut | thecignagroup.com | 72,400 | 247,100,000,000 | David Cordani |
| 15 | 23230 | 38 | -77 | 8,304 | POINT (-77.49153 37.587) | 3,290,323 | Altria | Tobacco | Richmond | Virginia | altria.com | 6,200 | 20,400,000,000 | William Gifford Jr. |
| 16 | 95032 | 37 | -122 | 27,682 | POINT (-121.92359 37.20859) | 2,785,714 | Netflix | Entertainment | Los Gatos | California | netflix.com | 14,000 | 39,000,000,000 | Ted Sarandos |
| 17 | 85251 | 33 | -112 | 39,976 | POINT (-111.92025 33.49406) | 2,733,333 | Taylor Morrison Home | Homebuilders | Scottsdale | Arizona | taylormorrison.com | 3,000 | 8,200,000,000 | Sheryl Palmer |
| 18 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | 2,729,032 | Goldman Sachs | Commercial Banks | New York | New York | goldmansachs.com | 46,500 | 126,900,000,000 | David Solomon |
| 19 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | 2,631,579 | Super Micro Computer | Computers, Office Equipment | San Jose | California | supermicro.com | 5,700 | 15,000,000,000 | Charles Liang |
| 20 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | 2,604,444 | Nationwide | Insurance: Property and Casualty (Mutual) | Columbus | Ohio | nationwide.com | 22,500 | 58,600,000,000 | Kirt Walker |
| 21 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | 2,267,442 | TD Synnex | Wholesalers: Electronics and Office Equipment | Fremont | California | tdsynnex.com | 25,800 | 58,500,000,000 | Patrick Zammit |
| 22 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | 2,219,973 | Meta | Internet Services and Retailing | Menlo Park | California | meta.com | 74,100 | 164,500,000,000 | Mark Zuckerberg |
| 23 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | 2,114,035 | Block | Financial Data Services | Oakland | California | block.xyz | 11,400 | 24,100,000,000 | Jack Dorsey |
| 24 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | 2,017,857 | Cincinnati Financial | Insurance: Property and Casualty (Stock) | Fairfield | Ohio | cinfin.com | 5,600 | 11,300,000,000 | Stephen Spray |
| 25 | 02210 | 42 | -71 | 6,554 | POINT (-71.03942 42.34815) | 1,803,279 | Vertex Pharmaceuticals | Pharmaceuticals | Boston | Massachusetts | vrtx.com | 6,100 | 11,000,000,000 | Reshma Kewalramani |
| 26 | 55126 | 45 | -93 | 27,484 | POINT (-93.13581 45.08614) | 1,800,000 | Land O'Lakes | Food Consumer Products | Arden Hills | Minnesota | landolakesinc.com | 9,000 | 16,200,000,000 | Beth Ford |
| 27 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | 1,543,103 | Murphy USA | Specialty Retailers: Other | El Dorado | Arkansas | murphyusa.com | 11,600 | 17,900,000,000 | Andrew Clyde |
| 28 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | 1,486,413 | Performance Food | Wholesalers: Food and Grocery | Richmond | Virginia | pfgc.com | 36,800 | 54,700,000,000 | George Holm |
| 29 | 33408 | 27 | -80 | 18,766 | POINT (-80.05677 26.84115) | 1,476,190 | NextEra Energy | Utilities: Gas and Electric | Juno Beach | Florida | nexteraenergy.com | 16,800 | 24,800,000,000 | John Ketchum |
| 30 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | 1,390,728 | CDW | Information Technology Services | Vernon Hills | Illinois | cdw.com | 15,100 | 21,000,000,000 | Christine Leahy |
| 31 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | 1,353,414 | Verizon | Telecommunications | New York | New York | verizon.com | 99,600 | 134,800,000,000 | Hans Vestberg |
| 32 | 46804 | 41 | -85 | 29,177 | POINT (-85.23913 41.05421) | 1,346,154 | Steel Dynamics | Metals | Fort Wayne | Indiana | steeldynamics.com | 13,000 | 17,500,000,000 | Mark Millett |
| 33 | 28211 | 35 | -81 | 32,637 | POINT (-80.79604 35.16816) | 1,314,815 | Sonic Automotive | Automotive Retailing, Services | Charlotte | North Carolina | sonicautomotive.com | 10,800 | 14,200,000,000 | David Bruton Smith |
| 34 | 55347 | 45 | -93 | 30,467 | POINT (-93.46638 44.82931) | 1,282,609 | C.H. Robinson Worldwide | Transportation and Logistics | Eden Prairie | Minnesota | chrobinson.com | 13,800 | 17,700,000,000 | David Bozeman |
| 35 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | 1,250,000 | Monster Beverage | Beverages | Corona | California | monsterbevcorp.com | 6,000 | 7,500,000,000 | Rodney Sacks |
| 36 | 48674 | 44 | -84 | 42,547 | POINT (-84.23229 43.70732) | 1,194,444 | Dow | Chemicals | Midland | Michigan | dow.com | 36,000 | 43,000,000,000 | James Fitterling |
| 37 | 48265 | 42 | -83 | 4,503 | POINT (-83.0456 42.3317) | 1,156,790 | General Motors | Motor Vehicles & Parts | Detroit | Michigan | gm.com | 162,000 | 187,400,000,000 | Mary Barra |
| 38 | 98052 | 48 | -122 | 79,074 | POINT (-122.1203 47.68148) | 1,075,000 | Microsoft | Computer Software | Redmond | Washington | microsoft.com | 228,000 | 245,100,000,000 | Satya Nadella |
| 39 | 61265 | 41 | -90 | 43,851 | POINT (-90.48895 41.48195) | 931,532 | Deere | Construction and Farm Machinery | Moline | Illinois | deere.com | 55,500 | 51,700,000,000 | John May |
| 40 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | 777,778 | Procter & Gamble | Household and Personal Products | Cincinnati | Ohio | pginvestor.com | 108,000 | 84,000,000,000 | Jon Moeller |
| 41 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | 764,264 | Costco | General Merchandisers | Issaquah | Washington | costco.com | 333,000 | 254,500,000,000 | Ron Vachris |
| 42 | 80021 | 40 | -105 | 35,562 | POINT (-105.11448 39.89105) | 756,250 | Ball | Packaging, Containers | Westminster | Colorado | ball.com | 16,000 | 12,100,000,000 | Daniel Fisher |
| 43 | 68179 | 41 | -96 | 0 | POINT (-95.9352 41.2597) | 746,914 | Union Pacific | Railroads | Omaha | Nebraska | up.com | 32,400 | 24,200,000,000 | Jim Vena |
| 44 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | 730,189 | General Electric | Aerospace & Defense | Evendale | Ohio | ge.com | 53,000 | 38,700,000,000 | Lawrence Culp Jr. |
| 45 | 53212 | 43 | -88 | 29,099 | POINT (-87.90845 43.07464) | 670,412 | Manpower | Diversified Outsourcing Services | Milwaukee | Wisconsin | manpowergroup.com | 26,700 | 17,900,000,000 | Jonas Prising |
| 46 | 97005 | 45 | -123 | 27,812 | POINT (-122.80397 45.49144) | 647,355 | Nike | Apparel | Beaverton | Oregon | nike.com | 79,400 | 51,400,000,000 | Elliott Hill |
| 47 | 35242 | 33 | -87 | 56,956 | POINT (-86.67073 33.42371) | 616,667 | Vulcan Materials | Building Materials, Glass | Birmingham | Alabama | vulcanmaterials.com | 12,000 | 7,400,000,000 | Thomas Hill |
| 48 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | 605,948 | Fluor | Engineering & Construction | Irving | Texas | fluor.com | 26,900 | 16,300,000,000 | James Breuer |
| 49 | 30354 | 34 | -84 | 15,487 | POINT (-84.38609 33.66058) | 598,058 | Delta Airlines | Airlines | Atlanta | Georgia | delta.com | 103,000 | 61,600,000,000 | Edward Bastian |
| 50 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | 595,133 | Cisco Systems | Network and Other Communications Equipment | San Jose | California | cisco.com | 90,400 | 53,800,000,000 | Charles Robbins |
| 51 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | 584,950 | Walgreens | Food & Drug Stores | Deerfield | Illinois | walgreensbootsalliance.com | 252,500 | 147,700,000,000 | Timothy Wentworth |
| 52 | 94086 | 37 | -122 | 48,956 | POINT (-122.02316 37.37164) | 538,462 | Intuitive Surgical | Medical Products and Equipment | Sunnyvale | California | intuitive.com | 15,600 | 8,400,000,000 | Gary Guthart |
| 53 | 33418 | 27 | -80 | 42,979 | POINT (-80.16641 26.86077) | 516,667 | Carrier Global | Industrial Machinery | Palm Beach Gardens | Florida | carrier.com | 48,000 | 24,800,000,000 | David Gitlin |
| 54 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | 487,719 | Baker Hughes | Oil and Gas Equipment, Services | Houston | Texas | bakerhughes.com | 57,000 | 27,800,000,000 | Lorenzo Simonelli |
| 55 | 48152 | 42 | -83 | 30,394 | POINT (-83.37433 42.42597) | 433,333 | Masco | Home Equipment, Furnishings | Livonia | Michigan | masco.com | 18,000 | 7,800,000,000 | Keith Allman |
| 56 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | 422,594 | News Corp. | Publishing, Printing | New York | New York | newscorp.com | 23,900 | 10,100,000,000 | Robert Thomson |
| 57 | 85054 | 34 | -112 | 10,159 | POINT (-111.94763 33.67515) | 380,952 | Republic Services | Waste Management | Phoenix | Arizona | republicservices.com | 42,000 | 16,000,000,000 | Jon Vander Ark |
| 58 | 49022 | 42 | -86 | 29,796 | POINT (-86.3675 42.11434) | 377,273 | Whirlpool | Electronics, Electrical Equip. | Benton Harbor | Michigan | whirlpoolcorp.com | 44,000 | 16,600,000,000 | Marc Bitzer |
| 59 | 72745 | 36 | -94 | 14,521 | POINT (-94.10046 36.2477) | 360,119 | J.B. Hunt Transport Services | Trucking, Truck Leasing | Lowell | Arkansas | jbhunt.com | 33,600 | 12,100,000,000 | Shelley Simpson |
| 60 | 02451 | 42 | -71 | 18,153 | POINT (-71.2573 42.39859) | 343,200 | Thermo Fisher Scientific | Scientific, Photographic and Control Equipment | Waltham | Massachusetts | thermofisher.com | 125,000 | 42,900,000,000 | Marc Casper |
| 61 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | 281,796 | Las Vegas Sands | Hotels, Casinos, Resorts | Las Vegas | Nevada | sands.com | 40,100 | 11,300,000,000 | Robert Goldstein |
| 62 | 98390 | 47 | -122 | 11,497 | POINT (-122.22894 47.21195) | 271,795 | Lululemon athletica | Specialty Retailers: Apparel | Sumner | Washington | lululemon.com | 39,000 | 10,600,000,000 | Calvin McDonald |
| 63 | 37203 | 36 | -87 | 20,234 | POINT (-86.78986 36.14937) | 260,517 | HCA Healthcare | Health Care: Medical Facilities | Nashville | Tennessee | hcahealthcare.com | 271,000 | 70,600,000,000 | Samuel Hazen |
| 64 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | 244,761 | UPS | Mail, Package and Freight Delivery | Atlanta | Georgia | ups.com | 372,200 | 91,100,000,000 | Carol Tomé |
| 65 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | 236,593 | Yum Brands | Food Services | Louisville | Kentucky | yum.com | 31,700 | 7,500,000,000 | David Gibbs |
| 66 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | 209,613 | Omnicom | Advertising, Marketing | New York | New York | omnicomgroup.com | 74,900 | 15,700,000,000 | John Wren |
In [121]:
minsmaxeffco = gdfstsinsmaxeffco.explore(column='Efficiency', name='The Most Efficient Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxeffco.explore(m=minsmaxeffco, column='Efficiency', name='The Most Efficient Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxeffco)
minsmaxeffco
Out[121]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [122]:
# Check the Most Efficient Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
pd.set_option('display.max_rows',None)
dfstmaxeffin = df.iloc[0:1]
for st in stslist[0:]:
dftemp = df.where(df['State'] == st[0]).dropna()
dftemp.insert(6,'Efficiency',1)
dftemp['Efficiency'] = dftemp['Revenue (rounded)'] / dftemp['Employees']
dfstmaxeffin = pd.concat([dfstmaxeffin, dftemp.groupby(['State','Industry'], as_index=False).sum('Efficiency').sort_values('Efficiency', ascending=False).head(1)])
dfstmaxeffin = dfstmaxeffin.iloc[1:]
dfstmaxeffin = dfstmaxeffin[['State','Industry','Efficiency']].sort_values(by=['Efficiency'], ascending=False).reset_index(drop=True)
dfstmaxeffin10 = dfstmaxeffin.head(10)
dfstmaxeffin
Out[122]:
| State | Industry | Efficiency | |
|---|---|---|---|
| 0 | Texas | Petroleum Refining | 43,606,030 |
| 1 | New York | Diversified Financials | 28,300,270 |
| 2 | California | Wholesalers: Diversified | 19,400,000 |
| 3 | District of Columbia | Diversified Financials | 18,621,951 |
| 4 | Virginia | Diversified Financials | 15,074,074 |
| 5 | Ohio | Real Estate | 11,428,571 |
| 6 | Florida | Energy | 8,978,723 |
| 7 | New Jersey | Petroleum Refining | 8,487,179 |
| 8 | Oklahoma | Mining, Crude-Oil Production | 6,913,043 |
| 9 | Pennsylvania | Wholesalers: Health Care | 6,681,818 |
| 10 | Colorado | Mining, Crude-Oil Production | 6,592,342 |
| 11 | Tennessee | Petroleum Refining | 6,250,000 |
| 12 | Missouri | Insurance: Life, Health (Stock) | 5,390,244 |
| 13 | Wisconsin | Insurance: Life, Health (Mutual) | 5,048,780 |
| 14 | Massachusetts | Energy | 4,980,743 |
| 15 | Minnesota | Food Production | 3,672,897 |
| 16 | Connecticut | Health Care: Pharmacy and Other Services | 3,412,983 |
| 17 | Michigan | Motor Vehicles & Parts | 2,907,881 |
| 18 | Arizona | Homebuilders | 2,733,333 |
| 19 | Illinois | Food Production | 2,639,881 |
| 20 | Georgia | Homebuilders | 2,632,353 |
| 21 | North Carolina | Commercial Banks | 2,450,342 |
| 22 | Nebraska | Insurance: Life, Health (Mutual) | 2,246,154 |
| 23 | Rhode Island | Insurance: Property and Casualty (Stock) | 1,793,103 |
| 24 | Kentucky | Health Care: Insurance and Managed Care | 1,792,998 |
| 25 | Indiana | Health Care: Insurance and Managed Care | 1,706,847 |
| 26 | Maryland | Energy | 1,661,972 |
| 27 | Washington | Internet Services and Retailing | 1,559,276 |
| 28 | Arkansas | Specialty Retailers: Other | 1,543,103 |
| 29 | Oregon | Automotive Retailing, Services | 1,211,921 |
| 30 | Louisiana | Utilities: Gas and Electric | 967,480 |
| 31 | Iowa | Insurance: Life, Health (Stock) | 817,259 |
| 32 | Nevada | Hotels, Casinos, Resorts | 757,071 |
| 33 | Kansas | Food Production | 650,000 |
| 34 | Alabama | Building Materials, Glass | 616,667 |
| 35 | Idaho | Semiconductors and Other Electronic Components | 522,917 |
| 36 | Delaware | Chemicals | 516,667 |
In [123]:
dfstmaxeffin10 = dfstmaxeffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxeffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)
Out[123]:
| State | Industry | Company | Zip Code | Efficiency | |
|---|---|---|---|---|---|
| 0 | Texas | Petroleum Refining | Exxon Mobil | 77389 | 43,606,030 |
| 1 | Texas | Petroleum Refining | Phillips 66 | 77042 | 43,606,030 |
| 2 | Texas | Petroleum Refining | Valero Energy | 78249 | 43,606,030 |
| 3 | Texas | Petroleum Refining | HF Sinclair | 75219 | 43,606,030 |
| 4 | Texas | Petroleum Refining | Par Pacific | 77024 | 43,606,030 |
| 5 | Texas | Petroleum Refining | Chevron | 77002 | 43,606,030 |
| 6 | New York | Diversified Financials | Blackstone | 10154 | 28,300,270 |
| 7 | New York | Diversified Financials | Voya Financial | 10169 | 28,300,270 |
| 8 | New York | Diversified Financials | Jefferies Financial | 10022 | 28,300,270 |
| 9 | New York | Diversified Financials | Marsh & McLennan | 10036 | 28,300,270 |
| 10 | New York | Diversified Financials | American Express | 10285 | 28,300,270 |
| 11 | New York | Diversified Financials | StoneX | 10169 | 28,300,270 |
| 12 | California | Wholesalers: Diversified | A-Mark Precious Metals | 90245 | 19,400,000 |
| 13 | District of Columbia | Diversified Financials | Fannie Mae | 20005 | 18,621,951 |
| 14 | Virginia | Diversified Financials | Freddie Mac | 22102 | 15,074,074 |
| 15 | Ohio | Real Estate | Welltower | 43615 | 11,428,571 |
| 16 | Florida | Energy | World Kinect | 33178 | 8,978,723 |
| 17 | New Jersey | Petroleum Refining | PBF Energy | 07054 | 8,487,179 |
| 18 | Oklahoma | Mining, Crude-Oil Production | Devon Energy | 73102 | 6,913,043 |
| 19 | Pennsylvania | Wholesalers: Health Care | Cencora | 19428 | 6,681,818 |
In [124]:
gdfstsstmaxeffin10 = gdfsts.merge(dfstmaxeffin10, how = 'inner', on = ['State'])
gdfusactstmaxeffin10 = gdfusact.merge(dfstmaxeffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactstmaxeffin10
Out[124]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Industry | Efficiency | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | Petroleum Refining | 43,606,030 | Phillips 66 |
| 1 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Texas | Petroleum Refining | 43,606,030 | Valero Energy |
| 2 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | Petroleum Refining | 43,606,030 | Exxon Mobil |
| 3 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Texas | Petroleum Refining | 43,606,030 | HF Sinclair |
| 4 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Petroleum Refining | 43,606,030 | Chevron |
| 5 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | Petroleum Refining | 43,606,030 | Par Pacific |
| 6 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | New York | Diversified Financials | 28,300,270 | American Express |
| 7 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | Diversified Financials | 28,300,270 | Marsh & McLennan |
| 8 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | New York | Diversified Financials | 28,300,270 | Blackstone |
| 9 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | Diversified Financials | 28,300,270 | StoneX |
| 10 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | Diversified Financials | 28,300,270 | Voya Financial |
| 11 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | Diversified Financials | 28,300,270 | Jefferies Financial |
| 12 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | California | Wholesalers: Diversified | 19,400,000 | A-Mark Precious Metals |
| 13 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | District of Columbia | Diversified Financials | 18,621,951 | Fannie Mae |
| 14 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | Diversified Financials | 15,074,074 | Freddie Mac |
| 15 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | Ohio | Real Estate | 11,428,571 | Welltower |
| 16 | 33178 | 26 | -80 | 65,515 | POINT (-80.4213 25.83578) | Florida | Energy | 8,978,723 | World Kinect |
| 17 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | New Jersey | Petroleum Refining | 8,487,179 | PBF Energy |
| 18 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Oklahoma | Mining, Crude-Oil Production | 6,913,043 | Devon Energy |
| 19 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Pennsylvania | Wholesalers: Health Care | 6,681,818 | Cencora |
In [125]:
mstmaxeffin = gdfstsstmaxeffin10.explore(column='Efficiency', name='The Most Efficient Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactstmaxeffin10.explore(m=mstmaxeffin, column='Efficiency', name='The Most Efficient Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxeffin)
mstmaxeffin
Out[125]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
# Conclusion:
# 1. Even though California is known with its Silicon Valley and movie Industry, but the Most Efficient one is not one of them. It's Wholesalers: Diversified.
# 2. Even though New York state has many companies in Commercial Banks Industry, turns out the Most Efficient one is Diversified Financials.
# 3. Many energy-related Companies are identified as the Most Efficient Industry.
In [126]:
# Check the Least Efficient Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
pd.set_option('display.max_rows',None)
dfstmineffin = df.iloc[0:1]
for st in stslist[0:]:
dftemp = df.where(df['State'] == st[0]).dropna()
dftemp.insert(6,'Efficiency',1)
dftemp['Efficiency'] = dftemp['Revenue (rounded)'] / dftemp['Employees']
dfstmineffin = pd.concat([dfstmineffin, dftemp.groupby(['State','Industry'], as_index=False).sum('Efficiency').sort_values('Efficiency', ascending=True).head(1)])
dfstmineffin = dfstmineffin.iloc[1:]
dfstmineffin = dfstmineffin[['State','Industry','Efficiency']].sort_values(by=['Efficiency'], ascending=False).reset_index(drop=True)
dfstmineffin10 = dfstmineffin.head(10)
dfstmineffin
Out[126]:
| State | Industry | Efficiency | |
|---|---|---|---|
| 0 | Oklahoma | Pipelines | 5,983,422 |
| 1 | Nevada | Hotels, Casinos, Resorts | 757,071 |
| 2 | Kansas | Food Production | 650,000 |
| 3 | Oregon | Apparel | 647,355 |
| 4 | Nebraska | Engineering & Construction | 528,302 |
| 5 | Louisiana | Telecommunications | 524,000 |
| 6 | Delaware | Chemicals | 516,667 |
| 7 | Alabama | Commercial Banks | 479,592 |
| 8 | Iowa | Specialty Retailers: Other | 450,151 |
| 9 | Rhode Island | Aerospace & Defense | 402,941 |
| 10 | Idaho | Food & Drug Stores | 402,848 |
| 11 | Michigan | Electronics, Electrical Equip. | 377,273 |
| 12 | District of Columbia | Industrial Machinery | 373,913 |
| 13 | North Carolina | Health Care: Pharmacy and Other Services | 373,777 |
| 14 | Arkansas | General Merchandisers | 324,286 |
| 15 | Indiana | Packaging, Containers | 292,857 |
| 16 | Wisconsin | General Merchandisers | 270,000 |
| 17 | Georgia | Mail, Package and Freight Delivery | 244,761 |
| 18 | Minnesota | General Merchandisers | 242,273 |
| 19 | Kentucky | Food Services | 236,593 |
| 20 | Arizona | Food & Drug Stores | 220,000 |
| 21 | Tennessee | Mail, Package and Freight Delivery | 207,771 |
| 22 | Ohio | Diversified Outsourcing Services | 206,452 |
| 23 | Missouri | Specialty Retailers: Other | 195,093 |
| 24 | Illinois | Food Services | 172,667 |
| 25 | Colorado | Health Care: Medical Facilities | 168,421 |
| 26 | Maryland | Hotels, Casinos, Resorts | 161,935 |
| 27 | Massachusetts | Specialty Retailers: Apparel | 154,945 |
| 28 | Connecticut | Network and Other Communications Equipment | 121,600 |
| 29 | Washington | Food Services | 100,277 |
| 30 | New York | Diversified Outsourcing Services | 71,795 |
| 31 | Pennsylvania | Diversified Outsourcing Services | 65,242 |
| 32 | Virginia | Hotels, Casinos, Resorts | 61,878 |
| 33 | Florida | Food Services | 59,655 |
| 34 | New Jersey | Information Technology Services | 58,492 |
| 35 | Texas | Food Services | 46,029 |
| 36 | California | Information Technology Services | 21,333 |
In [ ]:
# Conclusion:
# 1. Walmart as the Biggest Revenue Company and the Biggest Employer Company in State category, turns out, in terms of Efficiency,
# becomes one of the least.
# 2. Information Technology Services is the Lowest Efficient Industry. It's intriguing due to selling services is not the same as selling hardwares or softwares.
# It just needs skills, knowledges, and experiences. 😕
In [127]:
dfstmineffin10 = dfstmineffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmineffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)
Out[127]:
| State | Industry | Company | Zip Code | Efficiency | |
|---|---|---|---|---|---|
| 0 | Oklahoma | Pipelines | Oneok | 74103 | 5,983,422 |
| 1 | Oklahoma | Pipelines | Williams | 74172 | 5,983,422 |
| 2 | Nevada | Hotels, Casinos, Resorts | MGM Resorts International | 89109 | 757,071 |
| 3 | Nevada | Hotels, Casinos, Resorts | Las Vegas Sands | 89113 | 757,071 |
| 4 | Nevada | Hotels, Casinos, Resorts | Caesars Entertainment | 89501 | 757,071 |
| 5 | Kansas | Food Production | Seaboard | 66202 | 650,000 |
| 6 | Oregon | Apparel | Nike | 97005 | 647,355 |
| 7 | Nebraska | Engineering & Construction | Peter Kiewit Sons' | 68102 | 528,302 |
| 8 | Louisiana | Telecommunications | Lumen Technologies | 71203 | 524,000 |
| 9 | Delaware | Chemicals | DuPont | 19805 | 516,667 |
| 10 | Alabama | Commercial Banks | Regions Financial | 35203 | 479,592 |
| 11 | Iowa | Specialty Retailers: Other | Casey's General Stores | 50021 | 450,151 |
| 12 | Rhode Island | Aerospace & Defense | Textron | 02903 | 402,941 |
In [128]:
gdfstsstmineffin10 = gdfsts.merge(dfstmineffin10, how = 'inner', on = ['State'])
gdfusactstmineffin10 = gdfusact.merge(dfstmineffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactstmineffin10
Out[128]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Industry | Efficiency | Company | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 74103 | 36 | -96 | 2,419 | POINT (-95.9957 36.15617) | Oklahoma | Pipelines | 5,983,422 | Oneok |
| 1 | 74172 | 36 | -96 | 0 | POINT (-95.9905 36.1544) | Oklahoma | Pipelines | 5,983,422 | Williams |
| 2 | 89109 | 36 | -115 | 6,924 | POINT (-115.16327 36.12603) | Nevada | Hotels, Casinos, Resorts | 757,071 | MGM Resorts International |
| 3 | 89113 | 36 | -115 | 37,313 | POINT (-115.26236 36.06017) | Nevada | Hotels, Casinos, Resorts | 757,071 | Las Vegas Sands |
| 4 | 89501 | 40 | -120 | 3,641 | POINT (-119.81262 39.52602) | Nevada | Hotels, Casinos, Resorts | 757,071 | Caesars Entertainment |
| 5 | 66202 | 39 | -95 | 17,321 | POINT (-94.66909 39.02392) | Kansas | Food Production | 650,000 | Seaboard |
| 6 | 97005 | 45 | -123 | 27,812 | POINT (-122.80397 45.49144) | Oregon | Apparel | 647,355 | Nike |
| 7 | 68102 | 41 | -96 | 9,311 | POINT (-95.93224 41.26231) | Nebraska | Engineering & Construction | 528,302 | Peter Kiewit Sons' |
| 8 | 71203 | 33 | -92 | 38,770 | POINT (-92.01351 32.58398) | Louisiana | Telecommunications | 524,000 | Lumen Technologies |
| 9 | 19805 | 40 | -76 | 40,315 | POINT (-75.59373 39.74523) | Delaware | Chemicals | 516,667 | DuPont |
| 10 | 35203 | 34 | -87 | 3,301 | POINT (-86.80999 33.51847) | Alabama | Commercial Banks | 479,592 | Regions Financial |
| 11 | 50021 | 42 | -94 | 29,718 | POINT (-93.56838 41.7207) | Iowa | Specialty Retailers: Other | 450,151 | Casey's General Stores |
| 12 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Rhode Island | Aerospace & Defense | 402,941 | Textron |
In [129]:
mstmineffin10 = gdfstsstmineffin10.explore(column='Efficiency', name='The Least Efficient Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactstmineffin10.explore(m=mstmineffin10, column='Efficiency', name='The Least Efficient Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmineffin10)
mstmineffin10
Out[129]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [130]:
# The Most Efficient Industry in US
dfusmaxeffin = df.groupby(['Industry'], as_index=False).sum('Employees')
dfusmaxeffin.insert(3,'Efficiency',1)
dfusmaxeffin['Efficiency'] = dfusmaxeffin['Revenue (rounded)'] / dfusmaxeffin['Employees']
dfusmaxeffin = dfusmaxeffin.sort_values('Efficiency', ascending=False).reset_index(drop=True)[['Industry','Employees','Revenue (rounded)','Efficiency']]
dfusmaxeffin
Out[130]:
| Industry | Employees | Revenue (rounded) | Efficiency | |
|---|---|---|---|---|
| 0 | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 |
| 1 | Pipelines | 55200 | 268,400,000,000 | 4,862,319 |
| 2 | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 |
| 3 | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 |
| 4 | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 |
| 5 | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 |
| 6 | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 |
| 7 | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 |
| 8 | Wholesalers: Electronics and Office Equipment | 88900 | 158,200,000,000 | 1,779,528 |
| 9 | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 |
| 10 | Health Care: Insurance and Managed Care | 650300 | 908,000,000,000 | 1,396,279 |
| 11 | Energy | 121900 | 163,200,000,000 | 1,338,802 |
| 12 | Computers, Office Equipment | 447700 | 598,300,000,000 | 1,336,386 |
| 13 | Health Care: Pharmacy and Other Services | 572800 | 669,500,000,000 | 1,168,820 |
| 14 | Wholesalers: Food and Grocery | 186100 | 211,900,000,000 | 1,138,635 |
| 15 | Utilities: Gas and Electric | 306200 | 329,200,000,000 | 1,075,114 |
| 16 | Insurance: Property and Casualty (Stock) | 789100 | 842,900,000,000 | 1,068,179 |
| 17 | Securities | 172200 | 175,900,000,000 | 1,021,487 |
| 18 | Automotive Retailing, Services | 232000 | 215,700,000,000 | 929,741 |
| 19 | Food Production | 241400 | 222,800,000,000 | 922,949 |
| 20 | Pharmaceuticals | 549400 | 487,300,000,000 | 886,968 |
| 21 | Commercial Banks | 1577000 | 1,321,000,000,000 | 837,666 |
| 22 | Telecommunications | 566700 | 473,800,000,000 | 836,068 |
| 23 | Metals | 140900 | 116,600,000,000 | 827,537 |
| 24 | Entertainment | 338000 | 259,900,000,000 | 768,935 |
| 25 | Semiconductors and Other Electronic Components | 627900 | 446,900,000,000 | 711,738 |
| 26 | Beverages | 131200 | 91,600,000,000 | 698,171 |
| 27 | Computer Software | 565200 | 393,200,000,000 | 695,683 |
| 28 | Financial Data Services | 260100 | 175,300,000,000 | 673,972 |
| 29 | Railroads | 75500 | 50,800,000,000 | 672,848 |
| 30 | Wholesalers: Diversified | 255100 | 169,600,000,000 | 664,837 |
| 31 | Motor Vehicles & Parts | 893000 | 590,800,000,000 | 661,590 |
| 32 | Construction and Farm Machinery | 210900 | 138,900,000,000 | 658,606 |
| 33 | Tobacco | 89300 | 58,300,000,000 | 652,856 |
| 34 | Internet Services and Retailing | 2071800 | 1,330,100,000,000 | 642,002 |
| 35 | Household and Personal Products | 255000 | 155,300,000,000 | 609,020 |
| 36 | Apparel | 140500 | 79,600,000,000 | 566,548 |
| 37 | Chemicals | 379700 | 203,000,000,000 | 534,633 |
| 38 | Building Materials, Glass | 66000 | 34,800,000,000 | 527,273 |
| 39 | Airlines | 467900 | 221,400,000,000 | 473,178 |
| 40 | Aerospace & Defense | 911500 | 407,400,000,000 | 446,956 |
| 41 | Food Consumer Products | 604700 | 263,800,000,000 | 436,249 |
| 42 | Oil and Gas Equipment, Services | 139000 | 59,600,000,000 | 428,777 |
| 43 | Publishing, Printing | 23900 | 10,100,000,000 | 422,594 |
| 44 | Packaging, Containers | 191400 | 80,800,000,000 | 422,153 |
| 45 | Engineering & Construction | 240500 | 100,000,000,000 | 415,800 |
| 46 | Food & Drug Stores | 1148100 | 441,900,000,000 | 384,897 |
| 47 | Medical Products and Equipment | 501600 | 184,600,000,000 | 368,022 |
| 48 | Waste Management | 103700 | 38,100,000,000 | 367,406 |
| 49 | Trucking, Truck Leasing | 33600 | 12,100,000,000 | 360,119 |
| 50 | General Merchandisers | 3101200 | 1,116,800,000,000 | 360,119 |
| 51 | Industrial Machinery | 594700 | 207,800,000,000 | 349,420 |
| 52 | Network and Other Communications Equipment | 251700 | 87,800,000,000 | 348,828 |
| 53 | Real Estate | 273800 | 95,100,000,000 | 347,334 |
| 54 | Scientific, Photographic and Control Equipment | 125000 | 42,900,000,000 | 343,200 |
| 55 | Specialty Retailers: Other | 1558200 | 505,200,000,000 | 324,220 |
| 56 | Home Equipment, Furnishings | 83600 | 26,200,000,000 | 313,397 |
| 57 | Electronics, Electrical Equip. | 158300 | 46,000,000,000 | 290,587 |
| 58 | Transportation and Logistics | 251400 | 60,700,000,000 | 241,448 |
| 59 | Health Care: Medical Facilities | 573200 | 132,500,000,000 | 231,158 |
| 60 | Mail, Package and Freight Delivery | 794300 | 178,800,000,000 | 225,104 |
| 61 | Advertising, Marketing | 128200 | 26,400,000,000 | 205,928 |
| 62 | Specialty Retailers: Apparel | 669500 | 121,800,000,000 | 181,927 |
| 63 | Diversified Outsourcing Services | 564900 | 89,500,000,000 | 158,435 |
| 64 | Hotels, Casinos, Resorts | 495100 | 76,100,000,000 | 153,706 |
| 65 | Information Technology Services | 1478900 | 201,900,000,000 | 136,520 |
| 66 | Food Services | 1109800 | 103,600,000,000 | 93,350 |
In [ ]:
# Conclusion: Energy-related, Health Care, Insurance, and Construction are the Most Efficient Industries in US.
In [131]:
# Draw the 10 Most Efficient Industries in US
dfusmaxeffin10 = dfusmaxeffin.head(10)
dfusmaxeffin10 = dfusmaxeffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxeffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfstsusmaxeffin10 = gdfsts.merge(dfusmaxeffin10, how = 'inner', on = ['State'])
gdfusactusmaxeffin10 = gdfusact.merge(dfusmaxeffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffin10
Out[131]:
| Zip Code | Latitude | Longitude | Population | geometry | Industry | Employees | Revenue (rounded) | Efficiency | State | Company | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 37027 | 36 | -87 | 61,961 | POINT (-86.78439 35.99978) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Tennessee | Delek US |
| 1 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | Chevron |
| 2 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | Valero Energy |
| 3 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | Exxon Mobil |
| 4 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | Phillips 66 |
| 5 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | Par Pacific |
| 6 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Ohio | Marathon Petroleum |
| 7 | 07054 | 41 | -74 | 30,139 | POINT (-74.40239 40.85527) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | New Jersey | PBF Energy |
| 8 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Petroleum Refining | 160600 | 1,044,500,000,000 | 6,503,736 | Texas | HF Sinclair |
| 9 | 74103 | 36 | -96 | 2,419 | POINT (-95.9957 36.15617) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Oklahoma | Oneok |
| 10 | 75225 | 33 | -97 | 22,383 | POINT (-96.79109 32.86511) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Energy Transfer |
| 11 | 74172 | 36 | -96 | 0 | POINT (-95.9905 36.1544) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Oklahoma | Williams |
| 12 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Enterprise Products Partners |
| 13 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Targa Resources |
| 14 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Cheniere Energy |
| 15 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Kinder Morgan |
| 16 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Pipelines | 55200 | 268,400,000,000 | 4,862,319 | Texas | Plains GP |
| 17 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 | Virginia | Owens & Minor |
| 18 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 | Ohio | Cardinal Health |
| 19 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 | Texas | McKesson |
| 20 | 11747 | 41 | -73 | 19,826 | POINT (-73.40931 40.78372) | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 | New York | Henry Schein |
| 21 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Wholesalers: Health Care | 188600 | 853,200,000,000 | 4,523,860 | Pennsylvania | Cencora |
| 22 | 53202 | 43 | -88 | 26,269 | POINT (-87.89893 43.04561) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | Wisconsin | Northwestern Mutual |
| 23 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | New York | Guardian Life |
| 24 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | Nebraska | Mutual of Omaha Insurance |
| 25 | 01111 | 42 | -73 | 0 | POINT (-72.54793 42.11733) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | Massachusetts | Mass Mutual |
| 26 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | New York | TIAA |
| 27 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | Ohio | Western & Southern Financial |
| 28 | 10010 | 41 | -74 | 31,905 | POINT (-73.98243 40.73899) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | New York | New York Life Insurance |
| 29 | 55415 | 45 | -93 | 6,474 | POINT (-93.2578 44.97463) | Insurance: Life, Health (Mutual) | 70800 | 249,800,000,000 | 3,528,249 | Minnesota | Thrivent Financial for Lutherans |
| 30 | 19034 | 40 | -75 | 7,084 | POINT (-75.20953 40.13353) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Pennsylvania | Toll Brothers |
| 31 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Georgia | Pulte |
| 32 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Virginia | NVR |
| 33 | 85251 | 33 | -112 | 39,976 | POINT (-111.92025 33.49406) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Arizona | Taylor Morrison Home |
| 34 | 33126 | 26 | -80 | 47,038 | POINT (-80.30054 25.78061) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Florida | Lennar |
| 35 | 76011 | 33 | -97 | 22,297 | POINT (-97.08223 32.7543) | Homebuilders | 49800 | 119,800,000,000 | 2,405,622 | Texas | D.R. Horton |
| 36 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | New York | Hess |
| 37 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Texas | Diamondback Energy |
| 38 | 80202 | 40 | -105 | 18,233 | POINT (-104.99768 39.75156) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Colorado | Ovintiv |
| 39 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Texas | ConocoPhillips |
| 40 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Texas | Occidental Petroleum |
| 41 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Texas | APA |
| 42 | 80237 | 40 | -105 | 22,764 | POINT (-104.90178 39.63996) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Colorado | Newmont |
| 43 | 85004 | 33 | -112 | 11,178 | POINT (-112.06988 33.45159) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Arizona | Freeport-McMoRan |
| 44 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Texas | EOG Resources |
| 45 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Mining, Crude-Oil Production | 89000 | 210,700,000,000 | 2,367,416 | Oklahoma | Devon Energy |
| 46 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 | Ohio | Nationwide |
| 47 | 48917 | 43 | -85 | 32,029 | POINT (-84.63897 42.72509) | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 | Michigan | Auto-Owners Insurance |
| 48 | 61710 | 41 | -89 | 79,633 | POINT (-88.9894 40.516) | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 | Illinois | State Farm |
| 49 | 16530 | 42 | -80 | 94,831 | POINT (-80.08204 42.13039) | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 | Pennsylvania | Erie Insurance |
| 50 | 91367 | 34 | -119 | 45,427 | POINT (-118.61518 34.17708) | Insurance: Property and Casualty (Mutual) | 113800 | 226,100,000,000 | 1,986,819 | California | Farmers Insurance Exchange |
| 51 | 33160 | 26 | -80 | 43,225 | POINT (-80.13583 25.93234) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Florida | Icahn Enterprises |
| 52 | 55474 | 45 | -93 | 28,071 | POINT (-93.27 44.98) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Minnesota | Ameriprise Financial |
| 53 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | American Express |
| 54 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Virginia | Freddie Mac |
| 55 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | Blackstone |
| 56 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | District of Columbia | Fannie Mae |
| 57 | 48226 | 42 | -83 | 6,893 | POINT (-83.05034 42.33182) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Michigan | Ally Financial |
| 58 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | StoneX |
| 59 | 06902 | 41 | -74 | 72,915 | POINT (-73.54751 41.05949) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Connecticut | Synchrony Financial |
| 60 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Texas | Corebridge Financial |
| 61 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | Marsh & McLennan |
| 62 | 60008 | 42 | -88 | 22,949 | POINT (-88.0229 42.0739) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Illinois | Arthur J. Gallagher |
| 63 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | Illinois | Discover Financial |
| 64 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | Voya Financial |
| 65 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | Diversified Financials | 350100 | 627,600,000,000 | 1,792,631 | New York | Jefferies Financial |
| 66 | 85034 | 33 | -112 | 4,825 | POINT (-112.01989 33.43465) | Wholesalers: Electronics and Office Equipment | 88900 | 158,200,000,000 | 1,779,528 | Arizona | Avnet |
| 67 | 92612 | 34 | -118 | 33,706 | POINT (-117.82457 33.65984) | Wholesalers: Electronics and Office Equipment | 88900 | 158,200,000,000 | 1,779,528 | California | Ingram Micro |
| 68 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | Wholesalers: Electronics and Office Equipment | 88900 | 158,200,000,000 | 1,779,528 | California | TD Synnex |
| 69 | 80112 | 40 | -105 | 36,687 | POINT (-104.85854 39.57288) | Wholesalers: Electronics and Office Equipment | 88900 | 158,200,000,000 | 1,779,528 | Colorado | Arrow Electronics |
| 70 | 50392 | 42 | -94 | 15,018 | POINT (-93.628 41.5898) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Iowa | Principal Financial |
| 71 | 31999 | 32 | -85 | 3,469 | POINT (-84.98772 32.46078) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Georgia | Aflac |
| 72 | 32246 | 30 | -82 | 60,443 | POINT (-81.51782 30.29422) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Florida | GuideWell Mutual |
| 73 | 07102 | 41 | -74 | 12,954 | POINT (-74.17343 40.73576) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | New Jersey | Prudential Financial |
| 74 | 10166 | 41 | -74 | 0 | POINT (-73.9769 40.7531) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | New York | MetLife |
| 75 | 10105 | 41 | -74 | 0 | POINT (-73.978 40.7644) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | New York | Equitable |
| 76 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | California | Pacific Life |
| 77 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Missouri | Reinsurance of America |
| 78 | 37402 | 35 | -85 | 4,203 | POINT (-85.31553 35.04672) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Tennessee | Unum |
| 79 | 55101 | 45 | -93 | 7,937 | POINT (-93.08739 44.95111) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Minnesota | Securian Financial |
| 80 | 19087 | 40 | -75 | 33,770 | POINT (-75.40004 40.06172) | Insurance: Life, Health (Stock) | 178200 | 299,200,000,000 | 1,679,012 | Pennsylvania | Lincoln National |
In [132]:
musmaxeffin10 = gdfstsusmaxeffin10.explore(column='Efficiency', name='The Most Efficient Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffin10.explore(m=musmaxeffin10, column='Efficiency', name='The Most Efficient Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffin10)
musmaxeffin10
Out[132]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [133]:
# The Biggest Revenue City in US (other viewpoint)
dfusmaxrevct = df.groupby(['State','City'], as_index=False).sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfusmaxrevct10 = dfusmaxrevct.head(10)
dfusmaxrevct
Out[133]:
| State | City | Employees | Revenue (rounded) | |
|---|---|---|---|---|
| 0 | New York | New York | 2028200 | 1,820,500,000,000 |
| 1 | Texas | Houston | 557600 | 906,500,000,000 |
| 2 | Washington | Seattle | 2101600 | 744,900,000,000 |
| 3 | Arkansas | Bentonville | 2100000 | 681,000,000,000 |
| 4 | Georgia | Atlanta | 1233700 | 489,700,000,000 |
| 5 | Texas | Irving | 287000 | 462,000,000,000 |
| 6 | Nebraska | Omaha | 463100 | 427,000,000,000 |
| 7 | Minnesota | Eden Prairie | 413800 | 418,000,000,000 |
| 8 | California | Cupertino | 164000 | 391,000,000,000 |
| 9 | Texas | Spring | 121900 | 379,700,000,000 |
| 10 | Rhode Island | Woonsocket | 259500 | 372,800,000,000 |
| 11 | Illinois | Chicago | 724600 | 368,100,000,000 |
| 12 | Texas | Dallas | 590100 | 366,500,000,000 |
| 13 | California | Mountain View | 207500 | 366,300,000,000 |
| 14 | North Carolina | Charlotte | 422700 | 331,300,000,000 |
| 15 | California | San Francisco | 492000 | 296,000,000,000 |
| 16 | Pennsylvania | Conshohocken | 44000 | 294,000,000,000 |
| 17 | Ohio | Cincinnati | 593500 | 276,100,000,000 |
| 18 | California | Santa Clara | 250200 | 255,600,000,000 |
| 19 | Washington | Issaquah | 333000 | 254,500,000,000 |
| 20 | Connecticut | Bloomfield | 72400 | 247,100,000,000 |
| 21 | Washington | Redmond | 228000 | 245,100,000,000 |
| 22 | Indiana | Indianapolis | 172700 | 238,900,000,000 |
| 23 | Ohio | Dublin | 48400 | 226,800,000,000 |
| 24 | Michigan | Detroit | 182200 | 216,300,000,000 |
| 25 | Minnesota | Minneapolis | 573300 | 211,400,000,000 |
| 26 | Missouri | St. Louis | 160700 | 207,500,000,000 |
| 27 | Virginia | McLean | 275900 | 197,900,000,000 |
| 28 | District of Columbia | Washington | 93200 | 185,200,000,000 |
| 29 | Michigan | Dearborn | 171000 | 185,000,000,000 |
| 30 | Texas | San Antonio | 47900 | 172,600,000,000 |
| 31 | California | Menlo Park | 74100 | 164,500,000,000 |
| 32 | Illinois | Deerfield | 290500 | 162,800,000,000 |
| 33 | Virginia | Arlington | 367100 | 159,500,000,000 |
| 34 | California | San Jose | 248200 | 153,000,000,000 |
| 35 | Texas | Austin | 284700 | 150,700,000,000 |
| 36 | Pennsylvania | Philadelphia | 448700 | 141,100,000,000 |
| 37 | Ohio | Findlay | 18300 | 140,400,000,000 |
| 38 | Kentucky | Louisville | 134400 | 136,600,000,000 |
| 39 | Connecticut | Stamford | 225500 | 132,500,000,000 |
| 40 | Virginia | Richmond | 99300 | 127,000,000,000 |
| 41 | Tennessee | Memphis | 559900 | 124,800,000,000 |
| 42 | Illinois | Bloomington | 67400 | 123,000,000,000 |
| 43 | New York | Purchase | 354300 | 120,100,000,000 |
| 44 | Pennsylvania | Pittsburgh | 209800 | 119,200,000,000 |
| 45 | Massachusetts | Boston | 115500 | 106,400,000,000 |
| 46 | California | Palo Alto | 95000 | 106,000,000,000 |
| 47 | Idaho | Boise | 244600 | 104,300,000,000 |
| 48 | Wisconsin | Milwaukee | 106900 | 96,700,000,000 |
| 49 | Maryland | Bethesda | 276000 | 96,100,000,000 |
| 50 | Texas | Round Rock | 108000 | 95,600,000,000 |
| 51 | California | Burbank | 205000 | 91,400,000,000 |
| 52 | Ohio | Columbus | 58700 | 90,300,000,000 |
| 53 | Virginia | Reston | 220000 | 90,300,000,000 |
| 54 | New Jersey | New Brunswick | 138100 | 88,800,000,000 |
| 55 | Florida | Miami | 25300 | 85,200,000,000 |
| 56 | North Carolina | Mooresville | 215500 | 83,700,000,000 |
| 57 | New Jersey | Newark | 50900 | 80,700,000,000 |
| 58 | Ohio | Cleveland | 188400 | 79,300,000,000 |
| 59 | Ohio | Mayfield Village | 66300 | 75,400,000,000 |
| 60 | California | Fremont | 43200 | 73,400,000,000 |
| 61 | Arizona | Phoenix | 121000 | 73,000,000,000 |
| 62 | Florida | Jacksonville | 114900 | 71,700,000,000 |
| 63 | Tennessee | Nashville | 271000 | 70,600,000,000 |
| 64 | California | San Diego | 74800 | 64,600,000,000 |
| 65 | New Jersey | Rahway | 74000 | 64,200,000,000 |
| 66 | Illinois | Northbrook | 55200 | 64,100,000,000 |
| 67 | New York | Armonk | 284500 | 62,800,000,000 |
| 68 | Florida | Lakeland | 255000 | 60,200,000,000 |
| 69 | Massachusetts | Waltham | 128800 | 60,100,000,000 |
| 70 | Rhode Island | Providence | 79600 | 57,100,000,000 |
| 71 | Massachusetts | Framingham | 364000 | 56,400,000,000 |
| 72 | Illinois | North Chicago | 55000 | 56,300,000,000 |
| 73 | Massachusetts | Springfield | 21900 | 55,000,000,000 |
| 74 | Texas | Fort Worth | 133300 | 54,200,000,000 |
| 75 | New Jersey | Parsippany | 38200 | 54,200,000,000 |
| 76 | Arkansas | Springdale | 138000 | 53,300,000,000 |
| 77 | Illinois | Moline | 55500 | 51,700,000,000 |
| 78 | Oregon | Beaverton | 79400 | 51,400,000,000 |
| 79 | Colorado | Denver | 123800 | 51,200,000,000 |
| 80 | California | Oakland | 39800 | 48,500,000,000 |
| 81 | Minnesota | St. Paul | 115100 | 48,500,000,000 |
| 82 | New Jersey | Princeton | 34100 | 48,300,000,000 |
| 83 | California | Irvine | 26100 | 48,000,000,000 |
| 84 | Massachusetts | Cambridge | 84400 | 44,600,000,000 |
| 85 | Washington | Bellevue | 49000 | 44,300,000,000 |
| 86 | Florida | St. Petersburg | 157000 | 43,800,000,000 |
| 87 | Michigan | Midland | 36000 | 43,000,000,000 |
| 88 | Connecticut | Greenwich | 179600 | 42,800,000,000 |
| 89 | Illinois | Abbott Park | 114000 | 42,000,000,000 |
| 90 | Minnesota | Richfield | 85000 | 41,500,000,000 |
| 91 | Virginia | Newport News | 79000 | 41,100,000,000 |
| 92 | Virginia | Falls Church | 97000 | 41,000,000,000 |
| 93 | California | Long Beach | 18000 | 40,600,000,000 |
| 94 | Tennessee | Goodlettsville | 194200 | 40,600,000,000 |
| 95 | Minnesota | Inver Grove Heights | 10700 | 39,300,000,000 |
| 96 | California | Los Gatos | 14000 | 39,000,000,000 |
| 97 | Ohio | Evendale | 53000 | 38,700,000,000 |
| 98 | Connecticut | Norwalk | 64600 | 38,300,000,000 |
| 99 | Illinois | Rosemont | 30000 | 37,900,000,000 |
| 100 | Massachusetts | Marlborough | 86000 | 37,200,000,000 |
| 101 | Texas | Arlington | 14800 | 36,800,000,000 |
| 102 | Oregon | Medford | 30200 | 36,600,000,000 |
| 103 | Indiana | Columbus | 69600 | 34,100,000,000 |
| 104 | California | Thousand Oaks | 28000 | 33,400,000,000 |
| 105 | Oklahoma | Tulsa | 11000 | 32,200,000,000 |
| 106 | Ohio | Akron | 80300 | 31,900,000,000 |
| 107 | Virginia | Chesapeake | 139600 | 30,800,000,000 |
| 108 | California | Beverly Hills | 34200 | 30,700,000,000 |
| 109 | Michigan | Bloomfield Hills | 28900 | 30,500,000,000 |
| 110 | Georgia | Duluth | 39000 | 28,900,000,000 |
| 111 | California | Foster City | 17600 | 28,800,000,000 |
| 112 | Nevada | Las Vegas | 109100 | 28,500,000,000 |
| 113 | Colorado | Centennial | 21500 | 27,900,000,000 |
| 114 | Tennessee | Brentwood | 41000 | 27,400,000,000 |
| 115 | Virginia | Glen Allen | 45200 | 27,300,000,000 |
| 116 | California | Newport Beach | 134800 | 27,100,000,000 |
| 117 | Florida | Fort Lauderdale | 25100 | 26,800,000,000 |
| 118 | Connecticut | Hartford | 19100 | 26,500,000,000 |
| 119 | Texas | Westlake | 32100 | 26,000,000,000 |
| 120 | North Carolina | Raleigh | 65300 | 25,900,000,000 |
| 121 | Colorado | Englewood | 32700 | 25,800,000,000 |
| 122 | Illinois | Lake Forest | 40400 | 25,600,000,000 |
| 123 | Florida | Coral Gables | 82700 | 24,900,000,000 |
| 124 | Florida | Juno Beach | 16800 | 24,800,000,000 |
| 125 | Florida | Palm Beach Gardens | 48000 | 24,800,000,000 |
| 126 | Michigan | Auburn Hills | 100600 | 24,500,000,000 |
| 127 | Illinois | Riverwoods | 21000 | 23,600,000,000 |
| 128 | Maryland | Baltimore | 14200 | 23,600,000,000 |
| 129 | Michigan | Southfield | 173700 | 23,300,000,000 |
| 130 | Florida | Tampa | 36800 | 22,900,000,000 |
| 131 | Michigan | Portage | 53000 | 22,600,000,000 |
| 132 | Missouri | Chesterfield | 4100 | 22,100,000,000 |
| 133 | Arizona | Scottsdale | 19000 | 22,000,000,000 |
| 134 | Ohio | Maumee | 41900 | 21,600,000,000 |
| 135 | Florida | Melbourne | 47000 | 21,300,000,000 |
| 136 | Wisconsin | Madison | 11100 | 21,300,000,000 |
| 137 | California | Dublin | 107000 | 21,100,000,000 |
| 138 | Illinois | Vernon Hills | 15100 | 21,000,000,000 |
| 139 | Pennsylvania | Allentown | 29100 | 20,600,000,000 |
| 140 | New Jersey | Franklin Lakes | 74000 | 20,200,000,000 |
| 141 | New Jersey | Teaneck | 336800 | 19,700,000,000 |
| 142 | New Jersey | Roseland | 64000 | 19,200,000,000 |
| 143 | Ohio | Toledo | 25700 | 19,000,000,000 |
| 144 | Georgia | Columbus | 12700 | 18,900,000,000 |
| 145 | Pennsylvania | Radnor | 9800 | 18,400,000,000 |
| 146 | New York | Long Island City | 30700 | 18,300,000,000 |
| 147 | Arkansas | El Dorado | 11600 | 17,900,000,000 |
| 148 | California | Rosemead | 14000 | 17,600,000,000 |
| 149 | Indiana | Fort Wayne | 13000 | 17,500,000,000 |
| 150 | Alabama | Birmingham | 31600 | 16,800,000,000 |
| 151 | Missouri | Springfield | 85600 | 16,700,000,000 |
| 152 | Michigan | Benton Harbor | 44000 | 16,600,000,000 |
| 153 | Arizona | Chandler | 36600 | 16,300,000,000 |
| 154 | California | Redwood City | 27300 | 16,300,000,000 |
| 155 | Missouri | Des Peres | 55000 | 16,300,000,000 |
| 156 | Minnesota | Arden Hills | 9000 | 16,200,000,000 |
| 157 | Wisconsin | Menomonee Falls | 60000 | 16,200,000,000 |
| 158 | Iowa | Des Moines | 19700 | 16,100,000,000 |
| 159 | Oklahoma | Oklahoma City | 2300 | 15,900,000,000 |
| 160 | Illinois | Glenview | 44000 | 15,900,000,000 |
| 161 | Pennsylvania | King of Prussia | 87500 | 15,800,000,000 |
| 162 | Michigan | Lansing | 7300 | 15,800,000,000 |
| 163 | New Jersey | Summit | 22000 | 15,500,000,000 |
| 164 | California | Woodland Hills | 9900 | 15,500,000,000 |
| 165 | North Carolina | Durham | 88000 | 15,400,000,000 |
| 166 | Massachusetts | Burlington | 29400 | 15,400,000,000 |
| 167 | Connecticut | New Britain | 48500 | 15,400,000,000 |
| 168 | Connecticut | Wallingford | 125000 | 15,200,000,000 |
| 169 | Iowa | Ankeny | 33100 | 14,900,000,000 |
| 170 | Pennsylvania | Canonsburg | 32000 | 14,700,000,000 |
| 171 | Tennessee | Antioch | 47000 | 14,400,000,000 |
| 172 | Connecticut | Farmington | 72000 | 14,300,000,000 |
| 173 | New York | Tarrytown | 15100 | 14,200,000,000 |
| 174 | Virginia | Ashburn | 130000 | 13,700,000,000 |
| 175 | Arizona | Tempe | 17400 | 13,700,000,000 |
| 176 | New York | Buffalo | 22100 | 13,500,000,000 |
| 177 | Pennsylvania | Coraopolis | 37400 | 13,400,000,000 |
| 178 | Pennsylvania | Erie | 6700 | 13,200,000,000 |
| 179 | New York | Corning | 56300 | 13,100,000,000 |
| 180 | Louisiana | Monroe | 25000 | 13,100,000,000 |
| 181 | North Carolina | Burlington | 65400 | 13,000,000,000 |
| 182 | Tennessee | Chattanooga | 10900 | 12,900,000,000 |
| 183 | New York | Melville | 25000 | 12,700,000,000 |
| 184 | Tennessee | Franklin | 52500 | 12,600,000,000 |
| 185 | Delaware | Wilmington | 24000 | 12,400,000,000 |
| 186 | Indiana | Evansville | 42000 | 12,300,000,000 |
| 187 | Colorado | Westminster | 16000 | 12,100,000,000 |
| 188 | Arkansas | Lowell | 33600 | 12,100,000,000 |
| 189 | Minnesota | Austin | 20000 | 11,900,000,000 |
| 190 | Louisiana | New Orleans | 12300 | 11,900,000,000 |
| 191 | Florida | Plantation | 18000 | 11,900,000,000 |
| 192 | Illinois | Rolling Meadows | 56000 | 11,600,000,000 |
| 193 | Florida | Orlando | 191100 | 11,400,000,000 |
| 194 | Ohio | Fairfield | 5600 | 11,300,000,000 |
| 195 | Texas | Plano | 245500 | 11,300,000,000 |
| 196 | Nevada | Reno | 50000 | 11,300,000,000 |
| 197 | Illinois | Bolingbrook | 39000 | 11,300,000,000 |
| 198 | Pennsylvania | Hershey | 19300 | 11,200,000,000 |
| 199 | Texas | Midland | 2000 | 11,100,000,000 |
| 200 | Pennsylvania | Fort Washington | 4900 | 10,800,000,000 |
| 201 | Georgia | Calhoun | 41900 | 10,800,000,000 |
| 202 | Wisconsin | Oshkosh | 18500 | 10,700,000,000 |
| 203 | Washington | Sumner | 39000 | 10,600,000,000 |
| 204 | New Jersey | Burlington | 47300 | 10,600,000,000 |
| 205 | Rhode Island | Johnston | 5800 | 10,400,000,000 |
| 206 | Indiana | Elkhart | 22300 | 10,000,000,000 |
| 207 | New York | Victor | 9300 | 10,000,000,000 |
| 208 | Florida | Sunny Isles Beach | 15000 | 10,000,000,000 |
| 209 | New Jersey | Secaucus | 50500 | 9,900,000,000 |
| 210 | California | Milpitas | 15100 | 9,800,000,000 |
| 211 | Virginia | Herndon | 8100 | 9,800,000,000 |
| 212 | California | El Segundo | 500 | 9,700,000,000 |
| 213 | California | Newark | 450000 | 9,600,000,000 |
| 214 | New Jersey | Camden | 14400 | 9,600,000,000 |
| 215 | Michigan | Byron Center | 15000 | 9,500,000,000 |
| 216 | Illinois | Oak Brook | 12500 | 9,500,000,000 |
| 217 | Massachusetts | Wilmington | 24000 | 9,400,000,000 |
| 218 | Tennessee | Kingsport | 14000 | 9,400,000,000 |
| 219 | Kansas | Merriam | 14000 | 9,100,000,000 |
| 220 | Florida | Estero | 26000 | 9,000,000,000 |
| 221 | California | Manhattan Beach | 15100 | 9,000,000,000 |
| 222 | Ohio | Mentor | 35000 | 8,800,000,000 |
| 223 | California | San Mateo | 10200 | 8,500,000,000 |
| 224 | California | Sunnyvale | 15600 | 8,400,000,000 |
| 225 | California | Pleasanton | 20500 | 8,400,000,000 |
| 226 | Illinois | Downers Grove | 24000 | 8,400,000,000 |
| 227 | Minnesota | Maplewood | 22000 | 8,300,000,000 |
| 228 | Ohio | Orrville | 9000 | 8,200,000,000 |
| 229 | Ohio | Westerville | 31000 | 8,000,000,000 |
| 230 | Michigan | Livonia | 18000 | 7,800,000,000 |
| 231 | Texas | New Braunfels | 7900 | 7,800,000,000 |
| 232 | Indiana | Warsaw | 17000 | 7,700,000,000 |
| 233 | California | Corona | 6000 | 7,500,000,000 |
| 234 | Michigan | Jackson | 8300 | 7,500,000,000 |
| 235 | Minnesota | Winona | 21000 | 7,500,000,000 |
| 236 | Illinois | Westchester | 11200 | 7,400,000,000 |
In [135]:
dfusmaxrevct10 = dfusmaxrevct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])
gdfstsusmaxrevct10 = gdfsts.merge(dfusmaxrevct10, how = 'inner', on = ['State'])
gdfusactusmaxrevct10 = gdfusact.merge(dfusmaxrevct10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevct10
Out[135]:
| Zip Code | Latitude | Longitude | Population | geometry | State | City | Employees | Revenue (rounded) | Company | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | Pfizer |
| 1 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | New York | 2028200 | 1,820,500,000,000 | Sirius XM |
| 2 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | 1,820,500,000,000 | Interpublic |
| 3 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | 1,820,500,000,000 | Jefferies Financial |
| 4 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Verizon |
| 5 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Morgan Stanley |
| 6 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Paramount Global |
| 7 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Marsh & McLennan |
| 8 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Fox |
| 9 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | Hess |
| 10 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | New York | 2028200 | 1,820,500,000,000 | News Corp. |
| 11 | 10153 | 41 | -74 | 0 | POINT (-73.97244 40.76362) | New York | New York | 2028200 | 1,820,500,000,000 | Estée Lauder |
| 12 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | New York | New York | 2028200 | 1,820,500,000,000 | Blackstone |
| 13 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | New York | 2028200 | 1,820,500,000,000 | Voya Financial |
| 14 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | New York | New York | 2028200 | 1,820,500,000,000 | Goldman Sachs |
| 15 | 10041 | 41 | -74 | 6,217 | POINT (-74.01 40.7031) | New York | New York | 2028200 | 1,820,500,000,000 | S&P Global |
| 16 | 10105 | 41 | -74 | 0 | POINT (-73.978 40.7644) | New York | New York | 2028200 | 1,820,500,000,000 | Equitable |
| 17 | 10166 | 41 | -74 | 0 | POINT (-73.9769 40.7531) | New York | New York | 2028200 | 1,820,500,000,000 | MetLife |
| 18 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | KKR |
| 19 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | New York | New York | 2028200 | 1,820,500,000,000 | Bank of New York |
| 20 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | New York | New York | 2028200 | 1,820,500,000,000 | American Express |
| 21 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | New York | 2028200 | 1,820,500,000,000 | Colgate-Palmolive |
| 22 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | New York | 2028200 | 1,820,500,000,000 | StoneX |
| 23 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | New York | 2028200 | 1,820,500,000,000 | American International |
| 24 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | New York | 2028200 | 1,820,500,000,000 | Citi |
| 25 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | Foot Locker |
| 26 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | New York | 2028200 | 1,820,500,000,000 | Warner Bros. Discovery |
| 27 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | New York | 2028200 | 1,820,500,000,000 | Consolidated Edison |
| 28 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | Guardian Life |
| 29 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | BlackRock |
| 30 | 10006 | 41 | -74 | 4,475 | POINT (-74.01306 40.70949) | New York | New York | 2028200 | 1,820,500,000,000 | ABM Industries |
| 31 | 10010 | 41 | -74 | 31,905 | POINT (-73.98243 40.73899) | New York | New York | 2028200 | 1,820,500,000,000 | New York Life Insurance |
| 32 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | 1,820,500,000,000 | International Flavors & Fragrances |
| 33 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | New York | 2028200 | 1,820,500,000,000 | Macy's |
| 34 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | New York | 2028200 | 1,820,500,000,000 | Oscar Health |
| 35 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | JPMorgan Chase |
| 36 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | TIAA |
| 37 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | Travelers |
| 38 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | Kyndryl s |
| 39 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | Omnicom |
| 40 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | New York | 2028200 | 1,820,500,000,000 | PVH |
| 41 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | 1,820,500,000,000 | Apollo Global Management |
| 42 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | New York | 2028200 | 1,820,500,000,000 | Loews |
| 43 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Texas | Houston | 557600 | 906,500,000,000 | Corebridge Financial |
| 44 | 77008 | 30 | -95 | 40,155 | POINT (-95.41766 29.79856) | Texas | Houston | 557600 | 906,500,000,000 | Quanta Services |
| 45 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | KBR |
| 46 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | CenterPoint Energy |
| 47 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | NRG Energy |
| 48 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Kinder Morgan |
| 49 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Chevron |
| 50 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Enterprise Products Partners |
| 51 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Plains GP |
| 52 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | Houston | 557600 | 906,500,000,000 | Par Pacific |
| 53 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | EOG Resources |
| 54 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Waste Management |
| 55 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | Houston | 557600 | 906,500,000,000 | 1 Automotive |
| 56 | 77077 | 30 | -96 | 63,421 | POINT (-95.64189 29.75375) | Texas | Houston | 557600 | 906,500,000,000 | Sysco |
| 57 | 77032 | 30 | -95 | 13,536 | POINT (-95.34004 29.96523) | Texas | Houston | 557600 | 906,500,000,000 | Halliburton |
| 58 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | Houston | 557600 | 906,500,000,000 | Phillips 66 |
| 59 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | Houston | 557600 | 906,500,000,000 | APA |
| 60 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | Houston | 557600 | 906,500,000,000 | NOV |
| 61 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Texas | Houston | 557600 | 906,500,000,000 | Occidental Petroleum |
| 62 | 77056 | 30 | -95 | 23,314 | POINT (-95.46806 29.74849) | Texas | Houston | 557600 | 906,500,000,000 | Westlake |
| 63 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | Houston | 557600 | 906,500,000,000 | ConocoPhillips |
| 64 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | Houston | 557600 | 906,500,000,000 | Baker Hughes |
| 65 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Cheniere Energy |
| 66 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | Houston | 557600 | 906,500,000,000 | Targa Resources |
| 67 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | Seattle | 2101600 | 744,900,000,000 | Coupang |
| 68 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | Seattle | 2101600 | 744,900,000,000 | Nordstrom |
| 69 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Washington | Seattle | 2101600 | 744,900,000,000 | Amazon |
| 70 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Washington | Seattle | 2101600 | 744,900,000,000 | Expedia |
| 71 | 98134 | 48 | -122 | 779 | POINT (-122.33686 47.57691) | Washington | Seattle | 2101600 | 744,900,000,000 | Starbucks |
| 72 | 98188 | 47 | -122 | 26,769 | POINT (-122.27398 47.44754) | Washington | Seattle | 2101600 | 744,900,000,000 | Alaska Air |
| 73 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | Arkansas | Bentonville | 2100000 | 681,000,000,000 | Walmart |
| 74 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Home Depot |
| 75 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Southern |
| 76 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Norfolk Southern |
| 77 | 30313 | 34 | -84 | 10,845 | POINT (-84.39761 33.76369) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Coca-Cola |
| 78 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Pulte |
| 79 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Global Payments |
| 80 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | Atlanta | 1233700 | 489,700,000,000 | UPS |
| 81 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Intercontinental Exchange |
| 82 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Graphic Packaging |
| 83 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Newell Brands |
| 84 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Genuine Parts |
| 85 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Assurant |
| 86 | 30354 | 34 | -84 | 15,487 | POINT (-84.38609 33.66058) | Georgia | Atlanta | 1233700 | 489,700,000,000 | Delta Airlines |
| 87 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Celanese |
| 88 | 75038 | 33 | -97 | 33,097 | POINT (-96.97946 32.87231) | Texas | Irving | 287000 | 462,000,000,000 | Kimberly-Clark |
| 89 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | McKesson |
| 90 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Caterpillar |
| 91 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Vistra |
| 92 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Builders FirstSource |
| 93 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Fluor |
| 94 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | Irving | 287000 | 462,000,000,000 | Commercial Metals |
| 95 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | Nebraska | Omaha | 463100 | 427,000,000,000 | Mutual of Omaha Insurance |
| 96 | 68179 | 41 | -96 | 0 | POINT (-95.9352 41.2597) | Nebraska | Omaha | 463100 | 427,000,000,000 | Union Pacific |
| 97 | 68131 | 41 | -96 | 13,928 | POINT (-95.96479 41.26435) | Nebraska | Omaha | 463100 | 427,000,000,000 | Berkshire Hathaway |
| 98 | 68102 | 41 | -96 | 9,311 | POINT (-95.93224 41.26231) | Nebraska | Omaha | 463100 | 427,000,000,000 | Peter Kiewit Sons' |
| 99 | 55344 | 45 | -93 | 14,180 | POINT (-93.43037 44.86452) | Minnesota | Eden Prairie | 413800 | 418,000,000,000 | UnitedHealth |
| 100 | 55347 | 45 | -93 | 30,467 | POINT (-93.46638 44.82931) | Minnesota | Eden Prairie | 413800 | 418,000,000,000 | C.H. Robinson Worldwide |
| 101 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | California | Cupertino | 164000 | 391,000,000,000 | Apple |
| 102 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | Spring | 121900 | 379,700,000,000 | Hewlett Packard |
| 103 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | Spring | 121900 | 379,700,000,000 | Exxon Mobil |
In [136]:
musmaxrevct10 = gdfstsusmaxrevct10.explore(column='Revenue (rounded)', name='The Biggest Revenue City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevct10.explore(m=musmaxrevct10, column='Revenue (rounded)', name='The Biggest Revenue City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevct10)
musmaxrevct10
Out[136]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [137]:
# The Biggest Revenue State in US (other viewpoint)
dfusmaxrevst = df.groupby(['State'], as_index=False).sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfusmaxrevst10 = dfusmaxrevst.head(10)
dfusmaxrevst
Out[137]:
| State | Employees | Revenue (rounded) | |
|---|---|---|---|
| 0 | Texas | 2432800 | 2,680,800,000,000 |
| 1 | California | 2857700 | 2,399,300,000,000 |
| 2 | New York | 2825500 | 2,085,200,000,000 |
| 3 | Washington | 2750600 | 1,299,400,000,000 |
| 4 | Illinois | 1655400 | 1,040,200,000,000 |
| 5 | Ohio | 1255100 | 1,035,800,000,000 |
| 6 | Minnesota | 1269900 | 802,600,000,000 |
| 7 | Arkansas | 2283200 | 764,300,000,000 |
| 8 | Virginia | 1461200 | 738,400,000,000 |
| 9 | Pennsylvania | 929200 | 672,400,000,000 |
| 10 | Michigan | 838000 | 602,400,000,000 |
| 11 | Georgia | 1327300 | 548,300,000,000 |
| 12 | Connecticut | 806700 | 532,100,000,000 |
| 13 | North Carolina | 856900 | 469,300,000,000 |
| 14 | Florida | 1058700 | 448,700,000,000 |
| 15 | New Jersey | 944300 | 440,900,000,000 |
| 16 | Rhode Island | 344900 | 440,300,000,000 |
| 17 | Nebraska | 463100 | 427,000,000,000 |
| 18 | Massachusetts | 854000 | 384,500,000,000 |
| 19 | Indiana | 336600 | 320,500,000,000 |
| 20 | Tennessee | 1190500 | 312,700,000,000 |
| 21 | Missouri | 305400 | 262,600,000,000 |
| 22 | District of Columbia | 93200 | 185,200,000,000 |
| 23 | Wisconsin | 196500 | 144,900,000,000 |
| 24 | Kentucky | 134400 | 136,600,000,000 |
| 25 | Arizona | 194000 | 125,000,000,000 |
| 26 | Maryland | 290200 | 119,700,000,000 |
| 27 | Colorado | 194000 | 117,000,000,000 |
| 28 | Idaho | 244600 | 104,300,000,000 |
| 29 | Oregon | 109600 | 88,000,000,000 |
| 30 | Oklahoma | 13300 | 48,100,000,000 |
| 31 | Nevada | 159100 | 39,800,000,000 |
| 32 | Iowa | 52800 | 31,000,000,000 |
| 33 | Louisiana | 37300 | 25,000,000,000 |
| 34 | Alabama | 31600 | 16,800,000,000 |
| 35 | Delaware | 24000 | 12,400,000,000 |
| 36 | Kansas | 14000 | 9,100,000,000 |
In [138]:
dfusmaxrevst10 = dfusmaxrevst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])
gdfstsusmaxrevst10 = gdfsts.merge(dfusmaxrevst10, how = 'inner', on = ['State'])
gdfusactusmaxrevst10 = gdfusact.merge(dfusmaxrevst10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevst10
Out[138]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Employees | Revenue (rounded) | City | Company | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 75038 | 33 | -97 | 33,097 | POINT (-96.97946 32.87231) | Texas | 2432800 | 2,680,800,000,000 | Irving | Kimberly-Clark |
| 1 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | NOV |
| 2 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Cheniere Energy |
| 3 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Kinder Morgan |
| 4 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | CenterPoint Energy |
| 5 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | KBR |
| 6 | 77008 | 30 | -95 | 40,155 | POINT (-95.41766 29.79856) | Texas | 2432800 | 2,680,800,000,000 | Houston | Quanta Services |
| 7 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Texas | 2432800 | 2,680,800,000,000 | Houston | Corebridge Financial |
| 8 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | Houston | 1 Automotive |
| 9 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | Houston | Par Pacific |
| 10 | 77032 | 30 | -95 | 13,536 | POINT (-95.34004 29.96523) | Texas | 2432800 | 2,680,800,000,000 | Houston | Halliburton |
| 11 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | Phillips 66 |
| 12 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | APA |
| 13 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Texas | 2432800 | 2,680,800,000,000 | Houston | Occidental Petroleum |
| 14 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | EOG Resources |
| 15 | 77056 | 30 | -95 | 23,314 | POINT (-95.46806 29.74849) | Texas | 2432800 | 2,680,800,000,000 | Houston | Westlake |
| 16 | 77077 | 30 | -96 | 63,421 | POINT (-95.64189 29.75375) | Texas | 2432800 | 2,680,800,000,000 | Houston | Sysco |
| 17 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | Houston | ConocoPhillips |
| 18 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | Houston | Baker Hughes |
| 19 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | Spring | Exxon Mobil |
| 20 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | Spring | Hewlett Packard |
| 21 | 78130 | 30 | -98 | 95,787 | POINT (-98.06877 29.69224) | Texas | 2432800 | 2,680,800,000,000 | New Braunfels | Rush Enterprises |
| 22 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Texas | 2432800 | 2,680,800,000,000 | San Antonio | Valero Energy |
| 23 | 78725 | 30 | -98 | 10,810 | POINT (-97.60859 30.23554) | Texas | 2432800 | 2,680,800,000,000 | Austin | Tesla |
| 24 | 78741 | 30 | -98 | 45,274 | POINT (-97.71389 30.23007) | Texas | 2432800 | 2,680,800,000,000 | Austin | Oracle |
| 25 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Texas | 2432800 | 2,680,800,000,000 | Midland | Diamondback Energy |
| 26 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Waste Management |
| 27 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Targa Resources |
| 28 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | NRG Energy |
| 29 | 75202 | 33 | -97 | 2,744 | POINT (-96.8037 32.77843) | Texas | 2432800 | 2,680,800,000,000 | Dallas | AT&T |
| 30 | 78682 | 30 | -98 | 0 | POINT (-97.7273 30.4076) | Texas | 2432800 | 2,680,800,000,000 | Round Rock | Dell Technologies |
| 31 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | Texas | 2432800 | 2,680,800,000,000 | San Antonio | USAA |
| 32 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | McKesson |
| 33 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Caterpillar |
| 34 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Vistra |
| 35 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Builders FirstSource |
| 36 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Fluor |
| 37 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Celanese |
| 38 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Commercial Metals |
| 39 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | Texas | 2432800 | 2,680,800,000,000 | Plano | Yum China s |
| 40 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Plains GP |
| 41 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Jacobs Solutions |
| 42 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | Dallas | CBRE |
| 43 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Texas | 2432800 | 2,680,800,000,000 | Dallas | HF Sinclair |
| 44 | 76011 | 33 | -97 | 22,297 | POINT (-97.08223 32.7543) | Texas | 2432800 | 2,680,800,000,000 | Arlington | D.R. Horton |
| 45 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Enterprise Products Partners |
| 46 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Chevron |
| 47 | 75225 | 33 | -97 | 22,383 | POINT (-96.79109 32.86511) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Energy Transfer |
| 48 | 76155 | 33 | -97 | 6,301 | POINT (-97.04911 32.82404) | Texas | 2432800 | 2,680,800,000,000 | Fort Worth | American Airlines |
| 49 | 76262 | 33 | -97 | 43,589 | POINT (-97.22101 33.01137) | Texas | 2432800 | 2,680,800,000,000 | Westlake | Charles Schwab |
| 50 | 75254 | 33 | -97 | 24,737 | POINT (-96.80127 32.94571) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Tenet Healthcare |
| 51 | 75243 | 33 | -97 | 63,907 | POINT (-96.73633 32.91232) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Texas Instruments |
| 52 | 75240 | 33 | -97 | 24,718 | POINT (-96.78924 32.93194) | Texas | 2432800 | 2,680,800,000,000 | Dallas | AECOM |
| 53 | 75235 | 33 | -97 | 19,067 | POINT (-96.84798 32.83219) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Southwest Airlines |
| 54 | 91320 | 34 | -119 | 43,628 | POINT (-118.94795 34.17339) | California | 2857700 | 2,399,300,000,000 | Thousand Oaks | Amgen |
| 55 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | Beverly Hills | Live Nation Entertainment |
| 56 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | Beverly Hills | Endeavor |
| 57 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | California | 2857700 | 2,399,300,000,000 | El Segundo | A-Mark Precious Metals |
| 58 | 90266 | 34 | -118 | 34,584 | POINT (-118.39705 33.88968) | California | 2857700 | 2,399,300,000,000 | Manhattan Beach | Skechers U.S.A. |
| 59 | 90802 | 34 | -118 | 39,859 | POINT (-118.21143 33.75035) | California | 2857700 | 2,399,300,000,000 | Long Beach | Molina Healthcare |
| 60 | 91521 | 34 | -118 | 11,049 | POINT (-118.3252 34.1569) | California | 2857700 | 2,399,300,000,000 | Burbank | Walt Disney |
| 61 | 91367 | 34 | -119 | 45,427 | POINT (-118.61518 34.17708) | California | 2857700 | 2,399,300,000,000 | Woodland Hills | Farmers Insurance Exchange |
| 62 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Intel |
| 63 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | Fremont | TD Synnex |
| 64 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | California | 2857700 | 2,399,300,000,000 | Newark | Concentrix |
| 65 | 94568 | 38 | -122 | 70,542 | POINT (-121.90113 37.71596) | California | 2857700 | 2,399,300,000,000 | Dublin | Ross Stores |
| 66 | 94588 | 38 | -122 | 34,423 | POINT (-121.88178 37.73801) | California | 2857700 | 2,399,300,000,000 | Pleasanton | Workday |
| 67 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | Oakland | PG&E |
| 68 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | Oakland | Block |
| 69 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | California | 2857700 | 2,399,300,000,000 | Cupertino | Apple |
| 70 | 95032 | 37 | -122 | 27,682 | POINT (-121.92359 37.20859) | California | 2857700 | 2,399,300,000,000 | Los Gatos | Netflix |
| 71 | 95035 | 37 | -122 | 78,479 | POINT (-121.87632 37.44319) | California | 2857700 | 2,399,300,000,000 | Milpitas | KLA |
| 72 | 95051 | 37 | -122 | 61,345 | POINT (-121.98444 37.3483) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Nvidia |
| 73 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Applied Materials |
| 74 | 94403 | 38 | -122 | 43,459 | POINT (-122.30454 37.53844) | California | 2857700 | 2,399,300,000,000 | San Mateo | Franklin Resources |
| 75 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Advanced Micro Devices |
| 76 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | ServiceNow |
| 77 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Palo Alto Networks |
| 78 | 95110 | 37 | -122 | 19,444 | POINT (-121.9097 37.34656) | California | 2857700 | 2,399,300,000,000 | San Jose | Adobe |
| 79 | 95119 | 37 | -122 | 10,449 | POINT (-121.79077 37.22756) | California | 2857700 | 2,399,300,000,000 | San Jose | Western Digital |
| 80 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | California | 2857700 | 2,399,300,000,000 | San Jose | Ebay |
| 81 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | San Jose | PayPal |
| 82 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | San Jose | Super Micro Computer |
| 83 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | San Jose | Cisco Systems |
| 84 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | San Jose | Sanmina |
| 85 | 94404 | 38 | -122 | 35,950 | POINT (-122.26905 37.5562) | California | 2857700 | 2,399,300,000,000 | Foster City | Gilead Sciences |
| 86 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | Fremont | Lam Research |
| 87 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | Palo Alto | Broadcom |
| 88 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | Redwood City | Electronic Arts |
| 89 | 92101 | 33 | -117 | 48,163 | POINT (-117.18589 32.7162) | California | 2857700 | 2,399,300,000,000 | San Diego | Sempra |
| 90 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | San Diego | Qualcomm |
| 91 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | San Diego | LPL Financial s |
| 92 | 92612 | 34 | -118 | 33,706 | POINT (-117.82457 33.65984) | California | 2857700 | 2,399,300,000,000 | Irvine | Ingram Micro |
| 93 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | Newport Beach | Pacific Life |
| 94 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | Newport Beach | Chipotle Mexican Grill |
| 95 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | California | 2857700 | 2,399,300,000,000 | Corona | Monster Beverage |
| 96 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | California | 2857700 | 2,399,300,000,000 | Menlo Park | Meta |
| 97 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | Palo Alto | HP |
| 98 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | Mountain View | Intuit |
| 99 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | Redwood City | Equinix |
| 100 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | Mountain View | Alphabet |
| 101 | 94086 | 37 | -122 | 48,956 | POINT (-122.02316 37.37164) | California | 2857700 | 2,399,300,000,000 | Sunnyvale | Intuitive Surgical |
| 102 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | California | 2857700 | 2,399,300,000,000 | San Francisco | DoorDash |
| 103 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | California | 2857700 | 2,399,300,000,000 | San Francisco | Uber |
| 104 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | California | 2857700 | 2,399,300,000,000 | San Francisco | Airbnb |
| 105 | 94111 | 38 | -122 | 4,553 | POINT (-122.3998 37.79847) | California | 2857700 | 2,399,300,000,000 | San Francisco | Prologis |
| 106 | 94109 | 38 | -122 | 54,397 | POINT (-122.42138 37.79334) | California | 2857700 | 2,399,300,000,000 | San Francisco | Williams-Sonoma |
| 107 | 91770 | 34 | -118 | 58,893 | POINT (-118.08361 34.06395) | California | 2857700 | 2,399,300,000,000 | Rosemead | Edison International |
| 108 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Gap |
| 109 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Visa |
| 110 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Salesforce |
| 111 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | California | 2857700 | 2,399,300,000,000 | San Francisco | Wells Fargo |
| 112 | 10041 | 41 | -74 | 6,217 | POINT (-74.01 40.7031) | New York | 2825500 | 2,085,200,000,000 | New York | S&P Global |
| 113 | 10105 | 41 | -74 | 0 | POINT (-73.978 40.7644) | New York | 2825500 | 2,085,200,000,000 | New York | Equitable |
| 114 | 10166 | 41 | -74 | 0 | POINT (-73.9769 40.7531) | New York | 2825500 | 2,085,200,000,000 | New York | MetLife |
| 115 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | New York | 2825500 | 2,085,200,000,000 | New York | American Express |
| 116 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | New York | 2825500 | 2,085,200,000,000 | New York | Bank of New York |
| 117 | 14831 | 42 | -77 | 5,986 | POINT (-77.0553 42.1429) | New York | 2825500 | 2,085,200,000,000 | Corning | Corning |
| 118 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | KKR |
| 119 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Pfizer |
| 120 | 10591 | 41 | -74 | 23,663 | POINT (-73.84653 41.08436) | New York | 2825500 | 2,085,200,000,000 | Tarrytown | Regeneron Pharmaceuticals |
| 121 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Jefferies Financial |
| 122 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Colgate-Palmolive |
| 123 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | 2825500 | 2,085,200,000,000 | New York | Sirius XM |
| 124 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | 2825500 | 2,085,200,000,000 | New York | American International |
| 125 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | New York | 2825500 | 2,085,200,000,000 | Purchase | Mastercard |
| 126 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | Loews |
| 127 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | Apollo Global Management |
| 128 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | PVH |
| 129 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Omnicom |
| 130 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Kyndryl s |
| 131 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Travelers |
| 132 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | TIAA |
| 133 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | JPMorgan Chase |
| 134 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | 2825500 | 2,085,200,000,000 | New York | Oscar Health |
| 135 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | 2825500 | 2,085,200,000,000 | New York | Citi |
| 136 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Guardian Life |
| 137 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Foot Locker |
| 138 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | 2825500 | 2,085,200,000,000 | New York | Warner Bros. Discovery |
| 139 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | 2825500 | 2,085,200,000,000 | New York | Consolidated Edison |
| 140 | 10006 | 41 | -74 | 4,475 | POINT (-74.01306 40.70949) | New York | 2825500 | 2,085,200,000,000 | New York | ABM Industries |
| 141 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Interpublic |
| 142 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | International Flavors & Fragrances |
| 143 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Verizon |
| 144 | 10504 | 41 | -74 | 7,853 | POINT (-73.70629 41.13065) | New York | 2825500 | 2,085,200,000,000 | Armonk | IBM |
| 145 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Macy's |
| 146 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | BlackRock |
| 147 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | New York | 2825500 | 2,085,200,000,000 | Long Island City | JetBlue Airways |
| 148 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | New York | 2825500 | 2,085,200,000,000 | Long Island City | Altice USA |
| 149 | 11747 | 41 | -73 | 19,826 | POINT (-73.40931 40.78372) | New York | 2825500 | 2,085,200,000,000 | Melville | Henry Schein |
| 150 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Morgan Stanley |
| 151 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | New York | 2825500 | 2,085,200,000,000 | Buffalo | M&T Bank |
| 152 | 14564 | 43 | -77 | 16,257 | POINT (-77.42417 42.98329) | New York | 2825500 | 2,085,200,000,000 | Victor | Constellation Brands |
| 153 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | New York | 2825500 | 2,085,200,000,000 | Purchase | PepsiCo |
| 154 | 10010 | 41 | -74 | 31,905 | POINT (-73.98243 40.73899) | New York | 2825500 | 2,085,200,000,000 | New York | New York Life Insurance |
| 155 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | New York | 2825500 | 2,085,200,000,000 | New York | Goldman Sachs |
| 156 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | News Corp. |
| 157 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Paramount Global |
| 158 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Marsh & McLennan |
| 159 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | 2825500 | 2,085,200,000,000 | New York | Voya Financial |
| 160 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Hess |
| 161 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Fox |
| 162 | 10153 | 41 | -74 | 0 | POINT (-73.97244 40.76362) | New York | 2825500 | 2,085,200,000,000 | New York | Estée Lauder |
| 163 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | New York | 2825500 | 2,085,200,000,000 | New York | Blackstone |
| 164 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | 2825500 | 2,085,200,000,000 | New York | StoneX |
| 165 | 98052 | 48 | -122 | 79,074 | POINT (-122.1203 47.68148) | Washington | 2750600 | 1,299,400,000,000 | Redmond | Microsoft |
| 166 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | Washington | 2750600 | 1,299,400,000,000 | Issaquah | Costco |
| 167 | 98006 | 48 | -122 | 40,770 | POINT (-122.14957 47.55772) | Washington | 2750600 | 1,299,400,000,000 | Bellevue | Expeditors International of Washington |
| 168 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Coupang |
| 169 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Nordstrom |
| 170 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Amazon |
| 171 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Expedia |
| 172 | 98134 | 48 | -122 | 779 | POINT (-122.33686 47.57691) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Starbucks |
| 173 | 98188 | 47 | -122 | 26,769 | POINT (-122.27398 47.44754) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Alaska Air |
| 174 | 98390 | 47 | -122 | 11,497 | POINT (-122.22894 47.21195) | Washington | 2750600 | 1,299,400,000,000 | Sumner | Lululemon athletica |
| 175 | 98004 | 48 | -122 | 39,435 | POINT (-122.20548 47.61865) | Washington | 2750600 | 1,299,400,000,000 | Bellevue | Paccar |
| 176 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Mondelez |
| 177 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Conagra Brands |
| 178 | 60440 | 42 | -88 | 52,074 | POINT (-88.07572 41.70125) | Illinois | 1655400 | 1,040,200,000,000 | Bolingbrook | Ulta Beauty |
| 179 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Motorola Solutions |
| 180 | 61265 | 41 | -90 | 43,851 | POINT (-90.48895 41.48195) | Illinois | 1655400 | 1,040,200,000,000 | Moline | Deere |
| 181 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | McDonald's |
| 182 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Molson Coors Beverage |
| 183 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | United Airlines |
| 184 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Northern Trust |
| 185 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Exelon |
| 186 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Old Republic International |
| 187 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Jones Lang LaSalle |
| 188 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Kraft Heinz |
| 189 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Archer Daniels Midland |
| 190 | 60523 | 42 | -88 | 10,012 | POINT (-87.95406 41.83713) | Illinois | 1655400 | 1,040,200,000,000 | Oak Brook | Ace Hardware |
| 191 | 60515 | 42 | -88 | 29,045 | POINT (-88.0247 41.80991) | Illinois | 1655400 | 1,040,200,000,000 | Downers Grove | Dover |
| 192 | 60154 | 42 | -88 | 16,524 | POINT (-87.88986 41.84923) | Illinois | 1655400 | 1,040,200,000,000 | Westchester | Ingredion |
| 193 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Kellanova |
| 194 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | Illinois | 1655400 | 1,040,200,000,000 | Abbott Park | Abbott Laboratories |
| 195 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | Illinois | 1655400 | 1,040,200,000,000 | North Chicago | AbbVie |
| 196 | 60062 | 42 | -88 | 41,667 | POINT (-87.84235 42.12663) | Illinois | 1655400 | 1,040,200,000,000 | Northbrook | Allstate |
| 197 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | Illinois | 1655400 | 1,040,200,000,000 | Vernon Hills | CDW |
| 198 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Illinois | 1655400 | 1,040,200,000,000 | Lake Forest | Packaging Corp. of America |
| 199 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Illinois | 1655400 | 1,040,200,000,000 | Lake Forest | W.W. Grainger |
| 200 | 60025 | 42 | -88 | 40,877 | POINT (-87.81204 42.07466) | Illinois | 1655400 | 1,040,200,000,000 | Glenview | Illinois Tool Works |
| 201 | 60018 | 42 | -88 | 29,302 | POINT (-87.89846 41.99629) | Illinois | 1655400 | 1,040,200,000,000 | Rosemont | US Foods |
| 202 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Deerfield | Baxter International |
| 203 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Riverwoods | Discover Financial |
| 204 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Deerfield | Walgreens |
| 205 | 60008 | 42 | -88 | 22,949 | POINT (-88.0229 42.0739) | Illinois | 1655400 | 1,040,200,000,000 | Rolling Meadows | Arthur J. Gallagher |
| 206 | 61710 | 41 | -89 | 79,633 | POINT (-88.9894 40.516) | Illinois | 1655400 | 1,040,200,000,000 | Bloomington | State Farm |
| 207 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | GE HealthCare Technologies |
| 208 | 44143 | 42 | -81 | 24,337 | POINT (-81.47513 41.55358) | Ohio | 1255100 | 1,035,800,000,000 | Mayfield Village | Progressive |
| 209 | 44124 | 41 | -81 | 40,046 | POINT (-81.46774 41.49999) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Parker-Hannifin |
| 210 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | Ohio | 1255100 | 1,035,800,000,000 | Fairfield | Cincinnati Financial |
| 211 | 44308 | 41 | -82 | 1,261 | POINT (-81.51751 41.0818) | Ohio | 1255100 | 1,035,800,000,000 | Akron | FirstEnergy |
| 212 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Sherwin-Williams |
| 213 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | KeyCorp |
| 214 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Cleveland-Cliffs |
| 215 | 44060 | 42 | -81 | 60,257 | POINT (-81.32806 41.67742) | Ohio | 1255100 | 1,035,800,000,000 | Mentor | Avery Dennison |
| 216 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | Ohio | 1255100 | 1,035,800,000,000 | Toledo | Welltower |
| 217 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | Maumee | Dana |
| 218 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | Maumee | Andersons |
| 219 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | American Electric Power |
| 220 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | Nationwide |
| 221 | 43082 | 40 | -83 | 33,799 | POINT (-82.88437 40.15537) | Ohio | 1255100 | 1,035,800,000,000 | Westerville | Vertiv s |
| 222 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Ohio | 1255100 | 1,035,800,000,000 | Dublin | Cardinal Health |
| 223 | 44667 | 41 | -82 | 13,688 | POINT (-81.76495 40.83386) | Ohio | 1255100 | 1,035,800,000,000 | Orrville | J.M. Smucker |
| 224 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Kroger |
| 225 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Procter & Gamble |
| 226 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Western & Southern Financial |
| 227 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | American Financial |
| 228 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | Ohio | 1255100 | 1,035,800,000,000 | Evendale | General Electric |
| 229 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Ohio | 1255100 | 1,035,800,000,000 | Findlay | Marathon Petroleum |
| 230 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | Huntington Bancshares |
| 231 | 43659 | 42 | -84 | 0 | POINT (-83.5554 41.6639) | Ohio | 1255100 | 1,035,800,000,000 | Toledo | Owens Corning |
| 232 | 44316 | 41 | -81 | 0 | POINT (-81.47083 41.07854) | Ohio | 1255100 | 1,035,800,000,000 | Akron | Goodyear Tire & Rubber |
| 233 | 45262 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Cintas |
| 234 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Fifth Third Bancorp |
| 235 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | TransDigm |
| 236 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | 3M |
| 237 | 55474 | 45 | -93 | 28,071 | POINT (-93.27 44.98) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Ameriprise Financial |
| 238 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | Minnesota | 1269900 | 802,600,000,000 | Maplewood | Solventum |
| 239 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Target |
| 240 | 55126 | 45 | -93 | 27,484 | POINT (-93.13581 45.08614) | Minnesota | 1269900 | 802,600,000,000 | Arden Hills | Land O'Lakes |
| 241 | 55415 | 45 | -93 | 6,474 | POINT (-93.2578 44.97463) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Thrivent Financial for Lutherans |
| 242 | 55077 | 45 | -93 | 14,585 | POINT (-93.07574 44.81989) | Minnesota | 1269900 | 802,600,000,000 | Inver Grove Heights | CHS |
| 243 | 55101 | 45 | -93 | 7,937 | POINT (-93.08739 44.95111) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | Securian Financial |
| 244 | 55102 | 45 | -93 | 19,565 | POINT (-93.12149 44.93216) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | Ecolab |
| 245 | 55344 | 45 | -93 | 14,180 | POINT (-93.43037 44.86452) | Minnesota | 1269900 | 802,600,000,000 | Eden Prairie | UnitedHealth |
| 246 | 55347 | 45 | -93 | 30,467 | POINT (-93.46638 44.82931) | Minnesota | 1269900 | 802,600,000,000 | Eden Prairie | C.H. Robinson Worldwide |
| 247 | 55401 | 45 | -93 | 11,526 | POINT (-93.26984 44.98526) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Xcel Energy |
| 248 | 55402 | 45 | -93 | 760 | POINT (-93.27119 44.97608) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | U.S. Bancorp |
| 249 | 55987 | 44 | -92 | 33,911 | POINT (-91.63143 43.98469) | Minnesota | 1269900 | 802,600,000,000 | Winona | Fastenal |
| 250 | 55912 | 44 | -93 | 29,438 | POINT (-92.99148 43.6827) | Minnesota | 1269900 | 802,600,000,000 | Austin | Hormel Foods |
| 251 | 55426 | 45 | -93 | 25,451 | POINT (-93.38139 44.95635) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | General Mills |
| 252 | 55423 | 45 | -93 | 36,779 | POINT (-93.28144 44.87663) | Minnesota | 1269900 | 802,600,000,000 | Richfield | Best Buy |
| 253 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | Arkansas | 2283200 | 764,300,000,000 | Bentonville | Walmart |
| 254 | 72745 | 36 | -94 | 14,521 | POINT (-94.10046 36.2477) | Arkansas | 2283200 | 764,300,000,000 | Lowell | J.B. Hunt Transport Services |
| 255 | 72762 | 36 | -94 | 47,402 | POINT (-94.22794 36.18747) | Arkansas | 2283200 | 764,300,000,000 | Springdale | Tyson Foods |
| 256 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | Arkansas | 2283200 | 764,300,000,000 | El Dorado | Murphy USA |
| 257 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Virginia | 1461200 | 738,400,000,000 | Glen Allen | Owens & Minor |
| 258 | 23219 | 38 | -77 | 3,856 | POINT (-77.43484 37.54076) | Virginia | 1461200 | 738,400,000,000 | Richmond | Dominion Energy |
| 259 | 23227 | 38 | -77 | 25,574 | POINT (-77.44234 37.61486) | Virginia | 1461200 | 738,400,000,000 | Richmond | ARKO |
| 260 | 23230 | 38 | -77 | 8,304 | POINT (-77.49153 37.587) | Virginia | 1461200 | 738,400,000,000 | Richmond | Altria |
| 261 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Virginia | 1461200 | 738,400,000,000 | Richmond | Performance Food |
| 262 | 22203 | 39 | -77 | 25,921 | POINT (-77.1164 38.87377) | Virginia | 1461200 | 738,400,000,000 | Arlington | AES |
| 263 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Virginia | 1461200 | 738,400,000,000 | Richmond | CarMax |
| 264 | 23320 | 37 | -76 | 59,626 | POINT (-76.21807 36.75208) | Virginia | 1461200 | 738,400,000,000 | Chesapeake | Dollar Tree |
| 265 | 23606 | 37 | -76 | 29,899 | POINT (-76.49557 37.07847) | Virginia | 1461200 | 738,400,000,000 | Newport News | Ferguson |
| 266 | 23607 | 37 | -76 | 23,028 | POINT (-76.42235 36.98753) | Virginia | 1461200 | 738,400,000,000 | Newport News | Huntington Ingalls Industries |
| 267 | 22209 | 39 | -77 | 13,725 | POINT (-77.07309 38.89413) | Virginia | 1461200 | 738,400,000,000 | Arlington | RTX |
| 268 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Virginia | 1461200 | 738,400,000,000 | Glen Allen | Markel |
| 269 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | CACI International |
| 270 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | General Dynamics |
| 271 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Booz Allen Hamilton |
| 272 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Hilton |
| 273 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Capital One |
| 274 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Freddie Mac |
| 275 | 22042 | 39 | -77 | 34,631 | POINT (-77.19406 38.86463) | Virginia | 1461200 | 738,400,000,000 | Falls Church | Northrop Grumman |
| 276 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | Science Applications International |
| 277 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | NVR |
| 278 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | Leidos s |
| 279 | 20170 | 39 | -77 | 43,372 | POINT (-77.38042 38.98075) | Virginia | 1461200 | 738,400,000,000 | Herndon | QXO Building Products |
| 280 | 20147 | 39 | -77 | 67,007 | POINT (-77.47958 39.04151) | Virginia | 1461200 | 738,400,000,000 | Ashburn | DXC Technology |
| 281 | 22202 | 39 | -77 | 27,352 | POINT (-77.05175 38.8569) | Virginia | 1461200 | 738,400,000,000 | Arlington | Boeing |
| 282 | 15219 | 40 | -80 | 11,010 | POINT (-79.98443 40.44304) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | WESCO International |
| 283 | 15317 | 40 | -80 | 43,813 | POINT (-80.16535 40.27105) | Pennsylvania | 929200 | 672,400,000,000 | Canonsburg | Viatris |
| 284 | 15222 | 40 | -80 | 5,649 | POINT (-79.9912 40.44998) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | PNC |
| 285 | 15219 | 40 | -80 | 11,010 | POINT (-79.98443 40.44304) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | United States Steel |
| 286 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | Alcoa |
| 287 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | Howmet Aerospace |
| 288 | 15212 | 40 | -80 | 27,600 | POINT (-80.00844 40.47106) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | Westinghouse Air Brake Technologies |
| 289 | 18101 | 41 | -75 | 5,789 | POINT (-75.4698 40.60301) | Pennsylvania | 929200 | 672,400,000,000 | Allentown | PPL |
| 290 | 17033 | 40 | -77 | 17,009 | POINT (-76.62754 40.26829) | Pennsylvania | 929200 | 672,400,000,000 | Hershey | Hershey |
| 291 | 19103 | 40 | -75 | 25,602 | POINT (-75.17386 39.95303) | Pennsylvania | 929200 | 672,400,000,000 | Philadelphia | Aramark |
| 292 | 18106 | 41 | -76 | 6,437 | POINT (-75.59542 40.57472) | Pennsylvania | 929200 | 672,400,000,000 | Allentown | Air Products & Chemicals |
| 293 | 19034 | 40 | -75 | 7,084 | POINT (-75.20953 40.13353) | Pennsylvania | 929200 | 672,400,000,000 | Fort Washington | Toll Brothers |
| 294 | 19087 | 40 | -75 | 33,770 | POINT (-75.40004 40.06172) | Pennsylvania | 929200 | 672,400,000,000 | Radnor | Lincoln National |
| 295 | 16530 | 42 | -80 | 94,831 | POINT (-80.08204 42.13039) | Pennsylvania | 929200 | 672,400,000,000 | Erie | Erie Insurance |
| 296 | 15272 | 40 | -80 | 2,481 | POINT (-80.0048 40.44246) | Pennsylvania | 929200 | 672,400,000,000 | Pittsburgh | PPG Industries |
| 297 | 19103 | 40 | -75 | 25,602 | POINT (-75.17386 39.95303) | Pennsylvania | 929200 | 672,400,000,000 | Philadelphia | Comcast |
| 298 | 19406 | 40 | -75 | 29,388 | POINT (-75.38402 40.09467) | Pennsylvania | 929200 | 672,400,000,000 | King of Prussia | Universal Health Services |
| 299 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Pennsylvania | 929200 | 672,400,000,000 | Conshohocken | Cencora |
| 300 | 15108 | 41 | -80 | 42,782 | POINT (-80.20031 40.50006) | Pennsylvania | 929200 | 672,400,000,000 | Coraopolis | Dick's Sporting Goods |
In [139]:
musmaxrevst10 = gdfstsusmaxrevst10.explore(column='Revenue (rounded)', name='The Biggest Revenue State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevst10.explore(m=musmaxrevst10, column='Revenue (rounded)', name='The Biggest Revenue State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevst10)
musmaxrevst10
Out[139]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [140]:
# The Biggest Employer City in US (other viewpoint)
dfusmaxempct = df.groupby(['State','City'], as_index=False).sum('Employees').sort_values('Employees', ascending=False).reset_index(drop=True)
dfusmaxempct10 = dfusmaxempct.head(10)
dfusmaxempct
Out[140]:
| State | City | Employees | Revenue (rounded) | |
|---|---|---|---|---|
| 0 | Washington | Seattle | 2101600 | 744,900,000,000 |
| 1 | Arkansas | Bentonville | 2100000 | 681,000,000,000 |
| 2 | New York | New York | 2028200 | 1,820,500,000,000 |
| 3 | Georgia | Atlanta | 1233700 | 489,700,000,000 |
| 4 | Illinois | Chicago | 724600 | 368,100,000,000 |
| 5 | Ohio | Cincinnati | 593500 | 276,100,000,000 |
| 6 | Texas | Dallas | 590100 | 366,500,000,000 |
| 7 | Minnesota | Minneapolis | 573300 | 211,400,000,000 |
| 8 | Tennessee | Memphis | 559900 | 124,800,000,000 |
| 9 | Texas | Houston | 557600 | 906,500,000,000 |
| 10 | California | San Francisco | 492000 | 296,000,000,000 |
| 11 | Nebraska | Omaha | 463100 | 427,000,000,000 |
| 12 | California | Newark | 450000 | 9,600,000,000 |
| 13 | Pennsylvania | Philadelphia | 448700 | 141,100,000,000 |
| 14 | North Carolina | Charlotte | 422700 | 331,300,000,000 |
| 15 | Minnesota | Eden Prairie | 413800 | 418,000,000,000 |
| 16 | Virginia | Arlington | 367100 | 159,500,000,000 |
| 17 | Massachusetts | Framingham | 364000 | 56,400,000,000 |
| 18 | New York | Purchase | 354300 | 120,100,000,000 |
| 19 | New Jersey | Teaneck | 336800 | 19,700,000,000 |
| 20 | Washington | Issaquah | 333000 | 254,500,000,000 |
| 21 | Illinois | Deerfield | 290500 | 162,800,000,000 |
| 22 | Texas | Irving | 287000 | 462,000,000,000 |
| 23 | Texas | Austin | 284700 | 150,700,000,000 |
| 24 | New York | Armonk | 284500 | 62,800,000,000 |
| 25 | Maryland | Bethesda | 276000 | 96,100,000,000 |
| 26 | Virginia | McLean | 275900 | 197,900,000,000 |
| 27 | Tennessee | Nashville | 271000 | 70,600,000,000 |
| 28 | Rhode Island | Woonsocket | 259500 | 372,800,000,000 |
| 29 | Florida | Lakeland | 255000 | 60,200,000,000 |
| 30 | California | Santa Clara | 250200 | 255,600,000,000 |
| 31 | California | San Jose | 248200 | 153,000,000,000 |
| 32 | Texas | Plano | 245500 | 11,300,000,000 |
| 33 | Idaho | Boise | 244600 | 104,300,000,000 |
| 34 | Washington | Redmond | 228000 | 245,100,000,000 |
| 35 | Connecticut | Stamford | 225500 | 132,500,000,000 |
| 36 | Virginia | Reston | 220000 | 90,300,000,000 |
| 37 | North Carolina | Mooresville | 215500 | 83,700,000,000 |
| 38 | Pennsylvania | Pittsburgh | 209800 | 119,200,000,000 |
| 39 | California | Mountain View | 207500 | 366,300,000,000 |
| 40 | California | Burbank | 205000 | 91,400,000,000 |
| 41 | Tennessee | Goodlettsville | 194200 | 40,600,000,000 |
| 42 | Florida | Orlando | 191100 | 11,400,000,000 |
| 43 | Ohio | Cleveland | 188400 | 79,300,000,000 |
| 44 | Michigan | Detroit | 182200 | 216,300,000,000 |
| 45 | Connecticut | Greenwich | 179600 | 42,800,000,000 |
| 46 | Michigan | Southfield | 173700 | 23,300,000,000 |
| 47 | Indiana | Indianapolis | 172700 | 238,900,000,000 |
| 48 | Michigan | Dearborn | 171000 | 185,000,000,000 |
| 49 | California | Cupertino | 164000 | 391,000,000,000 |
| 50 | Missouri | St. Louis | 160700 | 207,500,000,000 |
| 51 | Florida | St. Petersburg | 157000 | 43,800,000,000 |
| 52 | Virginia | Chesapeake | 139600 | 30,800,000,000 |
| 53 | New Jersey | New Brunswick | 138100 | 88,800,000,000 |
| 54 | Arkansas | Springdale | 138000 | 53,300,000,000 |
| 55 | California | Newport Beach | 134800 | 27,100,000,000 |
| 56 | Kentucky | Louisville | 134400 | 136,600,000,000 |
| 57 | Texas | Fort Worth | 133300 | 54,200,000,000 |
| 58 | Virginia | Ashburn | 130000 | 13,700,000,000 |
| 59 | Massachusetts | Waltham | 128800 | 60,100,000,000 |
| 60 | Connecticut | Wallingford | 125000 | 15,200,000,000 |
| 61 | Colorado | Denver | 123800 | 51,200,000,000 |
| 62 | Texas | Spring | 121900 | 379,700,000,000 |
| 63 | Arizona | Phoenix | 121000 | 73,000,000,000 |
| 64 | Massachusetts | Boston | 115500 | 106,400,000,000 |
| 65 | Minnesota | St. Paul | 115100 | 48,500,000,000 |
| 66 | Florida | Jacksonville | 114900 | 71,700,000,000 |
| 67 | Illinois | Abbott Park | 114000 | 42,000,000,000 |
| 68 | Nevada | Las Vegas | 109100 | 28,500,000,000 |
| 69 | Texas | Round Rock | 108000 | 95,600,000,000 |
| 70 | California | Dublin | 107000 | 21,100,000,000 |
| 71 | Wisconsin | Milwaukee | 106900 | 96,700,000,000 |
| 72 | Michigan | Auburn Hills | 100600 | 24,500,000,000 |
| 73 | Virginia | Richmond | 99300 | 127,000,000,000 |
| 74 | Virginia | Falls Church | 97000 | 41,000,000,000 |
| 75 | California | Palo Alto | 95000 | 106,000,000,000 |
| 76 | District of Columbia | Washington | 93200 | 185,200,000,000 |
| 77 | North Carolina | Durham | 88000 | 15,400,000,000 |
| 78 | Pennsylvania | King of Prussia | 87500 | 15,800,000,000 |
| 79 | Massachusetts | Marlborough | 86000 | 37,200,000,000 |
| 80 | Missouri | Springfield | 85600 | 16,700,000,000 |
| 81 | Minnesota | Richfield | 85000 | 41,500,000,000 |
| 82 | Massachusetts | Cambridge | 84400 | 44,600,000,000 |
| 83 | Florida | Coral Gables | 82700 | 24,900,000,000 |
| 84 | Ohio | Akron | 80300 | 31,900,000,000 |
| 85 | Rhode Island | Providence | 79600 | 57,100,000,000 |
| 86 | Oregon | Beaverton | 79400 | 51,400,000,000 |
| 87 | Virginia | Newport News | 79000 | 41,100,000,000 |
| 88 | California | San Diego | 74800 | 64,600,000,000 |
| 89 | California | Menlo Park | 74100 | 164,500,000,000 |
| 90 | New Jersey | Rahway | 74000 | 64,200,000,000 |
| 91 | New Jersey | Franklin Lakes | 74000 | 20,200,000,000 |
| 92 | Connecticut | Bloomfield | 72400 | 247,100,000,000 |
| 93 | Connecticut | Farmington | 72000 | 14,300,000,000 |
| 94 | Indiana | Columbus | 69600 | 34,100,000,000 |
| 95 | Illinois | Bloomington | 67400 | 123,000,000,000 |
| 96 | Ohio | Mayfield Village | 66300 | 75,400,000,000 |
| 97 | North Carolina | Burlington | 65400 | 13,000,000,000 |
| 98 | North Carolina | Raleigh | 65300 | 25,900,000,000 |
| 99 | Connecticut | Norwalk | 64600 | 38,300,000,000 |
| 100 | New Jersey | Roseland | 64000 | 19,200,000,000 |
| 101 | Wisconsin | Menomonee Falls | 60000 | 16,200,000,000 |
| 102 | Ohio | Columbus | 58700 | 90,300,000,000 |
| 103 | New York | Corning | 56300 | 13,100,000,000 |
| 104 | Illinois | Rolling Meadows | 56000 | 11,600,000,000 |
| 105 | Illinois | Moline | 55500 | 51,700,000,000 |
| 106 | Illinois | Northbrook | 55200 | 64,100,000,000 |
| 107 | Illinois | North Chicago | 55000 | 56,300,000,000 |
| 108 | Missouri | Des Peres | 55000 | 16,300,000,000 |
| 109 | Ohio | Evendale | 53000 | 38,700,000,000 |
| 110 | Michigan | Portage | 53000 | 22,600,000,000 |
| 111 | Tennessee | Franklin | 52500 | 12,600,000,000 |
| 112 | New Jersey | Newark | 50900 | 80,700,000,000 |
| 113 | New Jersey | Secaucus | 50500 | 9,900,000,000 |
| 114 | Nevada | Reno | 50000 | 11,300,000,000 |
| 115 | Washington | Bellevue | 49000 | 44,300,000,000 |
| 116 | Connecticut | New Britain | 48500 | 15,400,000,000 |
| 117 | Ohio | Dublin | 48400 | 226,800,000,000 |
| 118 | Florida | Palm Beach Gardens | 48000 | 24,800,000,000 |
| 119 | Texas | San Antonio | 47900 | 172,600,000,000 |
| 120 | New Jersey | Burlington | 47300 | 10,600,000,000 |
| 121 | Tennessee | Antioch | 47000 | 14,400,000,000 |
| 122 | Florida | Melbourne | 47000 | 21,300,000,000 |
| 123 | Virginia | Glen Allen | 45200 | 27,300,000,000 |
| 124 | Pennsylvania | Conshohocken | 44000 | 294,000,000,000 |
| 125 | Michigan | Benton Harbor | 44000 | 16,600,000,000 |
| 126 | Illinois | Glenview | 44000 | 15,900,000,000 |
| 127 | California | Fremont | 43200 | 73,400,000,000 |
| 128 | Indiana | Evansville | 42000 | 12,300,000,000 |
| 129 | Georgia | Calhoun | 41900 | 10,800,000,000 |
| 130 | Ohio | Maumee | 41900 | 21,600,000,000 |
| 131 | Tennessee | Brentwood | 41000 | 27,400,000,000 |
| 132 | Illinois | Lake Forest | 40400 | 25,600,000,000 |
| 133 | California | Oakland | 39800 | 48,500,000,000 |
| 134 | Georgia | Duluth | 39000 | 28,900,000,000 |
| 135 | Illinois | Bolingbrook | 39000 | 11,300,000,000 |
| 136 | Washington | Sumner | 39000 | 10,600,000,000 |
| 137 | New Jersey | Parsippany | 38200 | 54,200,000,000 |
| 138 | Pennsylvania | Coraopolis | 37400 | 13,400,000,000 |
| 139 | Florida | Tampa | 36800 | 22,900,000,000 |
| 140 | Arizona | Chandler | 36600 | 16,300,000,000 |
| 141 | Michigan | Midland | 36000 | 43,000,000,000 |
| 142 | Ohio | Mentor | 35000 | 8,800,000,000 |
| 143 | California | Beverly Hills | 34200 | 30,700,000,000 |
| 144 | New Jersey | Princeton | 34100 | 48,300,000,000 |
| 145 | Arkansas | Lowell | 33600 | 12,100,000,000 |
| 146 | Iowa | Ankeny | 33100 | 14,900,000,000 |
| 147 | Colorado | Englewood | 32700 | 25,800,000,000 |
| 148 | Texas | Westlake | 32100 | 26,000,000,000 |
| 149 | Pennsylvania | Canonsburg | 32000 | 14,700,000,000 |
| 150 | Alabama | Birmingham | 31600 | 16,800,000,000 |
| 151 | Ohio | Westerville | 31000 | 8,000,000,000 |
| 152 | New York | Long Island City | 30700 | 18,300,000,000 |
| 153 | Oregon | Medford | 30200 | 36,600,000,000 |
| 154 | Illinois | Rosemont | 30000 | 37,900,000,000 |
| 155 | Massachusetts | Burlington | 29400 | 15,400,000,000 |
| 156 | Pennsylvania | Allentown | 29100 | 20,600,000,000 |
| 157 | Michigan | Bloomfield Hills | 28900 | 30,500,000,000 |
| 158 | California | Thousand Oaks | 28000 | 33,400,000,000 |
| 159 | California | Redwood City | 27300 | 16,300,000,000 |
| 160 | California | Irvine | 26100 | 48,000,000,000 |
| 161 | Florida | Estero | 26000 | 9,000,000,000 |
| 162 | Ohio | Toledo | 25700 | 19,000,000,000 |
| 163 | Florida | Miami | 25300 | 85,200,000,000 |
| 164 | Florida | Fort Lauderdale | 25100 | 26,800,000,000 |
| 165 | Louisiana | Monroe | 25000 | 13,100,000,000 |
| 166 | New York | Melville | 25000 | 12,700,000,000 |
| 167 | Delaware | Wilmington | 24000 | 12,400,000,000 |
| 168 | Illinois | Downers Grove | 24000 | 8,400,000,000 |
| 169 | Massachusetts | Wilmington | 24000 | 9,400,000,000 |
| 170 | Indiana | Elkhart | 22300 | 10,000,000,000 |
| 171 | New York | Buffalo | 22100 | 13,500,000,000 |
| 172 | Minnesota | Maplewood | 22000 | 8,300,000,000 |
| 173 | New Jersey | Summit | 22000 | 15,500,000,000 |
| 174 | Massachusetts | Springfield | 21900 | 55,000,000,000 |
| 175 | Colorado | Centennial | 21500 | 27,900,000,000 |
| 176 | Illinois | Riverwoods | 21000 | 23,600,000,000 |
| 177 | Minnesota | Winona | 21000 | 7,500,000,000 |
| 178 | California | Pleasanton | 20500 | 8,400,000,000 |
| 179 | Minnesota | Austin | 20000 | 11,900,000,000 |
| 180 | Iowa | Des Moines | 19700 | 16,100,000,000 |
| 181 | Pennsylvania | Hershey | 19300 | 11,200,000,000 |
| 182 | Connecticut | Hartford | 19100 | 26,500,000,000 |
| 183 | Arizona | Scottsdale | 19000 | 22,000,000,000 |
| 184 | Wisconsin | Oshkosh | 18500 | 10,700,000,000 |
| 185 | Ohio | Findlay | 18300 | 140,400,000,000 |
| 186 | California | Long Beach | 18000 | 40,600,000,000 |
| 187 | Florida | Plantation | 18000 | 11,900,000,000 |
| 188 | Michigan | Livonia | 18000 | 7,800,000,000 |
| 189 | California | Foster City | 17600 | 28,800,000,000 |
| 190 | Arizona | Tempe | 17400 | 13,700,000,000 |
| 191 | Indiana | Warsaw | 17000 | 7,700,000,000 |
| 192 | Florida | Juno Beach | 16800 | 24,800,000,000 |
| 193 | Colorado | Westminster | 16000 | 12,100,000,000 |
| 194 | California | Sunnyvale | 15600 | 8,400,000,000 |
| 195 | California | Manhattan Beach | 15100 | 9,000,000,000 |
| 196 | Illinois | Vernon Hills | 15100 | 21,000,000,000 |
| 197 | California | Milpitas | 15100 | 9,800,000,000 |
| 198 | New York | Tarrytown | 15100 | 14,200,000,000 |
| 199 | Michigan | Byron Center | 15000 | 9,500,000,000 |
| 200 | Florida | Sunny Isles Beach | 15000 | 10,000,000,000 |
| 201 | Texas | Arlington | 14800 | 36,800,000,000 |
| 202 | New Jersey | Camden | 14400 | 9,600,000,000 |
| 203 | Maryland | Baltimore | 14200 | 23,600,000,000 |
| 204 | Tennessee | Kingsport | 14000 | 9,400,000,000 |
| 205 | California | Rosemead | 14000 | 17,600,000,000 |
| 206 | Kansas | Merriam | 14000 | 9,100,000,000 |
| 207 | California | Los Gatos | 14000 | 39,000,000,000 |
| 208 | Indiana | Fort Wayne | 13000 | 17,500,000,000 |
| 209 | Georgia | Columbus | 12700 | 18,900,000,000 |
| 210 | Illinois | Oak Brook | 12500 | 9,500,000,000 |
| 211 | Louisiana | New Orleans | 12300 | 11,900,000,000 |
| 212 | Arkansas | El Dorado | 11600 | 17,900,000,000 |
| 213 | Illinois | Westchester | 11200 | 7,400,000,000 |
| 214 | Wisconsin | Madison | 11100 | 21,300,000,000 |
| 215 | Oklahoma | Tulsa | 11000 | 32,200,000,000 |
| 216 | Tennessee | Chattanooga | 10900 | 12,900,000,000 |
| 217 | Minnesota | Inver Grove Heights | 10700 | 39,300,000,000 |
| 218 | California | San Mateo | 10200 | 8,500,000,000 |
| 219 | California | Woodland Hills | 9900 | 15,500,000,000 |
| 220 | Pennsylvania | Radnor | 9800 | 18,400,000,000 |
| 221 | New York | Victor | 9300 | 10,000,000,000 |
| 222 | Ohio | Orrville | 9000 | 8,200,000,000 |
| 223 | Minnesota | Arden Hills | 9000 | 16,200,000,000 |
| 224 | Michigan | Jackson | 8300 | 7,500,000,000 |
| 225 | Virginia | Herndon | 8100 | 9,800,000,000 |
| 226 | Texas | New Braunfels | 7900 | 7,800,000,000 |
| 227 | Michigan | Lansing | 7300 | 15,800,000,000 |
| 228 | Pennsylvania | Erie | 6700 | 13,200,000,000 |
| 229 | California | Corona | 6000 | 7,500,000,000 |
| 230 | Rhode Island | Johnston | 5800 | 10,400,000,000 |
| 231 | Ohio | Fairfield | 5600 | 11,300,000,000 |
| 232 | Pennsylvania | Fort Washington | 4900 | 10,800,000,000 |
| 233 | Missouri | Chesterfield | 4100 | 22,100,000,000 |
| 234 | Oklahoma | Oklahoma City | 2300 | 15,900,000,000 |
| 235 | Texas | Midland | 2000 | 11,100,000,000 |
| 236 | California | El Segundo | 500 | 9,700,000,000 |
In [141]:
dfusmaxempct10 = dfusmaxempct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])
gdfstsusmaxempct10 = gdfsts.merge(dfusmaxempct10, how = 'inner', on = ['State'])
gdfusactusmaxempct10 = gdfusact.merge(dfusmaxempct10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempct10
gdfstsusmaxempct10
Out[141]:
| State | region | postal | latitude | longitude | geometry | City | Employees | Revenue (rounded) | Company | Zip Code | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | Target | 55403 |
| 1 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | U.S. Bancorp | 55402 |
| 2 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | General Mills | 55426 |
| 3 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | Ameriprise Financial | 55474 |
| 4 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | Xcel Energy | 55401 |
| 5 | Minnesota | Midwest | MN | 46 | -93 | POLYGON ((-89.95766 47.28691, -90.13175 47.292... | Minneapolis | 573300 | 211,400,000,000 | Thrivent Financial for Lutherans | 55415 |
| 6 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Amazon | 98109 |
| 7 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Starbucks | 98134 |
| 8 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Coupang | 98101 |
| 9 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Nordstrom | 98101 |
| 10 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Expedia | 98119 |
| 11 | Washington | West | WA | 47 | -120 | POLYGON ((-117.03143 48.99931, -117.02665 47.7... | Seattle | 2101600 | 744,900,000,000 | Alaska Air | 98188 |
| 12 | Arkansas | South | AR | 35 | -92 | POLYGON ((-89.66292 36.02307, -89.67351 35.94,... | Bentonville | 2100000 | 681,000,000,000 | Walmart | 72712 |
| 13 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | AT&T | 75202 |
| 14 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | Energy Transfer | 75225 |
| 15 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | CBRE | 75201 |
| 16 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | HF Sinclair | 75219 |
| 17 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | Southwest Airlines | 75235 |
| 18 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | Tenet Healthcare | 75254 |
| 19 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | Jacobs Solutions | 75201 |
| 20 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | AECOM | 75240 |
| 21 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Dallas | 590100 | 366,500,000,000 | Texas Instruments | 75243 |
| 22 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Chevron | 77002 |
| 23 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Phillips 66 | 77042 |
| 24 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Sysco | 77077 |
| 25 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | ConocoPhillips | 77079 |
| 26 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Enterprise Products Partners | 77002 |
| 27 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Plains GP | 77002 |
| 28 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | NRG Energy | 77002 |
| 29 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Baker Hughes | 77079 |
| 30 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Occidental Petroleum | 77046 |
| 31 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | EOG Resources | 77002 |
| 32 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Quanta Services | 77008 |
| 33 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Halliburton | 77032 |
| 34 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Waste Management | 77002 |
| 35 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | 1 Automotive | 77024 |
| 36 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Corebridge Financial | 77019 |
| 37 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Targa Resources | 77002 |
| 38 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Cheniere Energy | 77002 |
| 39 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Kinder Morgan | 77002 |
| 40 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Westlake | 77056 |
| 41 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | APA | 77042 |
| 42 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | NOV | 77042 |
| 43 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | CenterPoint Energy | 77002 |
| 44 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | Par Pacific | 77024 |
| 45 | Texas | South | TX | 31 | -99 | POLYGON ((-106.50734 31.75429, -106.61953 31.9... | Houston | 557600 | 906,500,000,000 | KBR | 77002 |
| 46 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Home Depot | 30339 |
| 47 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | UPS | 30328 |
| 48 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Delta Airlines | 30354 |
| 49 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Coca-Cola | 30313 |
| 50 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Southern | 30308 |
| 51 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Genuine Parts | 30339 |
| 52 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Pulte | 30326 |
| 53 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Norfolk Southern | 30308 |
| 54 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Assurant | 30339 |
| 55 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Intercontinental Exchange | 30328 |
| 56 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Global Payments | 30326 |
| 57 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Graphic Packaging | 30328 |
| 58 | Georgia | South | GA | 33 | -83 | POLYGON ((-85.00519 30.99069, -85.05442 31.108... | Atlanta | 1233700 | 489,700,000,000 | Newell Brands | 30328 |
| 59 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Archer Daniels Midland | 60601 |
| 60 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | United Airlines | 60606 |
| 61 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Mondelez | 60607 |
| 62 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | McDonald's | 60607 |
| 63 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Kraft Heinz | 60601 |
| 64 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Jones Lang LaSalle | 60601 |
| 65 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Exelon | 60603 |
| 66 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | GE HealthCare Technologies | 60661 |
| 67 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Northern Trust | 60603 |
| 68 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Kellanova | 60654 |
| 69 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Conagra Brands | 60654 |
| 70 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Molson Coors Beverage | 60606 |
| 71 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Motorola Solutions | 60661 |
| 72 | Illinois | Midwest | IL | 40 | -89 | POLYGON ((-91.43033 40.3686, -91.41023 40.5511... | Chicago | 724600 | 368,100,000,000 | Old Republic International | 60601 |
| 73 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | Kroger | 45202 |
| 74 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | Procter & Gamble | 45202 |
| 75 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | Western & Southern Financial | 45202 |
| 76 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | Fifth Third Bancorp | 45263 |
| 77 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | Cintas | 45262 |
| 78 | Ohio | Midwest | OH | 40 | -83 | POLYGON ((-84.82368 39.10653, -84.81787 39.799... | Cincinnati | 593500 | 276,100,000,000 | American Financial | 45202 |
| 79 | Tennessee | South | TN | 36 | -86 | POLYGON ((-90.24924 35.02083, -90.13493 35.113... | Memphis | 559900 | 124,800,000,000 | FedEx | 38120 |
| 80 | Tennessee | South | TN | 36 | -86 | POLYGON ((-90.24924 35.02083, -90.13493 35.113... | Memphis | 559900 | 124,800,000,000 | International Paper | 38197 |
| 81 | Tennessee | South | TN | 36 | -86 | POLYGON ((-90.24924 35.02083, -90.13493 35.113... | Memphis | 559900 | 124,800,000,000 | AutoZone | 38103 |
| 82 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | JPMorgan Chase | 10017 |
| 83 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Citi | 10013 |
| 84 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Verizon | 10036 |
| 85 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Goldman Sachs | 10282 |
| 86 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Morgan Stanley | 10036 |
| 87 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | StoneX | 10169 |
| 88 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | American Express | 10285 |
| 89 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | MetLife | 10166 |
| 90 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Pfizer | 10001 |
| 91 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | New York Life Insurance | 10010 |
| 92 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | TIAA | 10017 |
| 93 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Travelers | 10017 |
| 94 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Bank of New York | 10286 |
| 95 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Warner Bros. Discovery | 10003 |
| 96 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | KKR | 10001 |
| 97 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Paramount Global | 10036 |
| 98 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | American International | 10020 |
| 99 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Apollo Global Management | 10019 |
| 100 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Marsh & McLennan | 10036 |
| 101 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Macy's | 10001 |
| 102 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | BlackRock | 10001 |
| 103 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Colgate-Palmolive | 10022 |
| 104 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Loews | 10019 |
| 105 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Guardian Life | 10001 |
| 106 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Kyndryl s | 10017 |
| 107 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Omnicom | 10017 |
| 108 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Estée Lauder | 10153 |
| 109 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Consolidated Edison | 10003 |
| 110 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | S&P Global | 10041 |
| 111 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Fox | 10036 |
| 112 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Blackstone | 10154 |
| 113 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Hess | 10036 |
| 114 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Equitable | 10105 |
| 115 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | International Flavors & Fragrances | 10019 |
| 116 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Interpublic | 10022 |
| 117 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Jefferies Financial | 10022 |
| 118 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | News Corp. | 10036 |
| 119 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Oscar Health | 10013 |
| 120 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Sirius XM | 10020 |
| 121 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | PVH | 10017 |
| 122 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | ABM Industries | 10006 |
| 123 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Voya Financial | 10169 |
| 124 | New York | Northeast | NY | 43 | -75 | POLYGON ((-73.49794 42.05451, -73.55349 41.289... | New York | 2028200 | 1,820,500,000,000 | Foot Locker | 10001 |
In [142]:
musmaxempct10 = gdfstsusmaxempct10.explore(column='Employees', name='The Biggest Employer City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempct10.explore(m=musmaxempct10, column='Employees', name='The Biggest Employer City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempct10)
musmaxempct10
Out[142]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [143]:
# The Biggest Employer State in US (other viewpoint)
dfusmaxempst = df.groupby(['State'], as_index=False).sum('Employees').sort_values('Employees', ascending=False).reset_index(drop=True)
dfusmaxempst10 = dfusmaxempst.head(10)
dfusmaxempst
Out[143]:
| State | Employees | Revenue (rounded) | |
|---|---|---|---|
| 0 | California | 2857700 | 2,399,300,000,000 |
| 1 | New York | 2825500 | 2,085,200,000,000 |
| 2 | Washington | 2750600 | 1,299,400,000,000 |
| 3 | Texas | 2432800 | 2,680,800,000,000 |
| 4 | Arkansas | 2283200 | 764,300,000,000 |
| 5 | Illinois | 1655400 | 1,040,200,000,000 |
| 6 | Virginia | 1461200 | 738,400,000,000 |
| 7 | Georgia | 1327300 | 548,300,000,000 |
| 8 | Minnesota | 1269900 | 802,600,000,000 |
| 9 | Ohio | 1255100 | 1,035,800,000,000 |
| 10 | Tennessee | 1190500 | 312,700,000,000 |
| 11 | Florida | 1058700 | 448,700,000,000 |
| 12 | New Jersey | 944300 | 440,900,000,000 |
| 13 | Pennsylvania | 929200 | 672,400,000,000 |
| 14 | North Carolina | 856900 | 469,300,000,000 |
| 15 | Massachusetts | 854000 | 384,500,000,000 |
| 16 | Michigan | 838000 | 602,400,000,000 |
| 17 | Connecticut | 806700 | 532,100,000,000 |
| 18 | Nebraska | 463100 | 427,000,000,000 |
| 19 | Rhode Island | 344900 | 440,300,000,000 |
| 20 | Indiana | 336600 | 320,500,000,000 |
| 21 | Missouri | 305400 | 262,600,000,000 |
| 22 | Maryland | 290200 | 119,700,000,000 |
| 23 | Idaho | 244600 | 104,300,000,000 |
| 24 | Wisconsin | 196500 | 144,900,000,000 |
| 25 | Arizona | 194000 | 125,000,000,000 |
| 26 | Colorado | 194000 | 117,000,000,000 |
| 27 | Nevada | 159100 | 39,800,000,000 |
| 28 | Kentucky | 134400 | 136,600,000,000 |
| 29 | Oregon | 109600 | 88,000,000,000 |
| 30 | District of Columbia | 93200 | 185,200,000,000 |
| 31 | Iowa | 52800 | 31,000,000,000 |
| 32 | Louisiana | 37300 | 25,000,000,000 |
| 33 | Alabama | 31600 | 16,800,000,000 |
| 34 | Delaware | 24000 | 12,400,000,000 |
| 35 | Kansas | 14000 | 9,100,000,000 |
| 36 | Oklahoma | 13300 | 48,100,000,000 |
In [144]:
dfusmaxempst10 = dfusmaxempst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])
gdfstsusmaxempst10 = gdfsts.merge(dfusmaxempst10, how = 'inner', on = ['State'])
gdfusactusmaxempst10 = gdfusact.merge(dfusmaxempst10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempst10
Out[144]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Employees | Revenue (rounded) | City | Company | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 91521 | 34 | -118 | 11,049 | POINT (-118.3252 34.1569) | California | 2857700 | 2,399,300,000,000 | Burbank | Walt Disney |
| 1 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | Palo Alto | Broadcom |
| 2 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | California | 2857700 | 2,399,300,000,000 | San Francisco | Uber |
| 3 | 94111 | 38 | -122 | 4,553 | POINT (-122.3998 37.79847) | California | 2857700 | 2,399,300,000,000 | San Francisco | Prologis |
| 4 | 94109 | 38 | -122 | 54,397 | POINT (-122.42138 37.79334) | California | 2857700 | 2,399,300,000,000 | San Francisco | Williams-Sonoma |
| 5 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | California | 2857700 | 2,399,300,000,000 | San Francisco | DoorDash |
| 6 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Gap |
| 7 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Visa |
| 8 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | San Francisco | Salesforce |
| 9 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | California | 2857700 | 2,399,300,000,000 | San Francisco | Wells Fargo |
| 10 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | California | 2857700 | 2,399,300,000,000 | San Francisco | Airbnb |
| 11 | 94086 | 37 | -122 | 48,956 | POINT (-122.02316 37.37164) | California | 2857700 | 2,399,300,000,000 | Sunnyvale | Intuitive Surgical |
| 12 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | Redwood City | Electronic Arts |
| 13 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | Redwood City | Equinix |
| 14 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | Mountain View | Intuit |
| 15 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | Mountain View | Alphabet |
| 16 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | California | 2857700 | 2,399,300,000,000 | Menlo Park | Meta |
| 17 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | California | 2857700 | 2,399,300,000,000 | Corona | Monster Beverage |
| 18 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | Newport Beach | Chipotle Mexican Grill |
| 19 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | Newport Beach | Pacific Life |
| 20 | 92612 | 34 | -118 | 33,706 | POINT (-117.82457 33.65984) | California | 2857700 | 2,399,300,000,000 | Irvine | Ingram Micro |
| 21 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | San Diego | LPL Financial s |
| 22 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | San Diego | Qualcomm |
| 23 | 92101 | 33 | -117 | 48,163 | POINT (-117.18589 32.7162) | California | 2857700 | 2,399,300,000,000 | San Diego | Sempra |
| 24 | 91770 | 34 | -118 | 58,893 | POINT (-118.08361 34.06395) | California | 2857700 | 2,399,300,000,000 | Rosemead | Edison International |
| 25 | 91367 | 34 | -119 | 45,427 | POINT (-118.61518 34.17708) | California | 2857700 | 2,399,300,000,000 | Woodland Hills | Farmers Insurance Exchange |
| 26 | 91320 | 34 | -119 | 43,628 | POINT (-118.94795 34.17339) | California | 2857700 | 2,399,300,000,000 | Thousand Oaks | Amgen |
| 27 | 90802 | 34 | -118 | 39,859 | POINT (-118.21143 33.75035) | California | 2857700 | 2,399,300,000,000 | Long Beach | Molina Healthcare |
| 28 | 90266 | 34 | -118 | 34,584 | POINT (-118.39705 33.88968) | California | 2857700 | 2,399,300,000,000 | Manhattan Beach | Skechers U.S.A. |
| 29 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | California | 2857700 | 2,399,300,000,000 | El Segundo | A-Mark Precious Metals |
| 30 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | Beverly Hills | Endeavor |
| 31 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | Palo Alto | HP |
| 32 | 94403 | 38 | -122 | 43,459 | POINT (-122.30454 37.53844) | California | 2857700 | 2,399,300,000,000 | San Mateo | Franklin Resources |
| 33 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | ServiceNow |
| 34 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Intel |
| 35 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | San Jose | Sanmina |
| 36 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | San Jose | Cisco Systems |
| 37 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | San Jose | Super Micro Computer |
| 38 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | San Jose | PayPal |
| 39 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | California | 2857700 | 2,399,300,000,000 | San Jose | Ebay |
| 40 | 95119 | 37 | -122 | 10,449 | POINT (-121.79077 37.22756) | California | 2857700 | 2,399,300,000,000 | San Jose | Western Digital |
| 41 | 95110 | 37 | -122 | 19,444 | POINT (-121.9097 37.34656) | California | 2857700 | 2,399,300,000,000 | San Jose | Adobe |
| 42 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Palo Alto Networks |
| 43 | 94404 | 38 | -122 | 35,950 | POINT (-122.26905 37.5562) | California | 2857700 | 2,399,300,000,000 | Foster City | Gilead Sciences |
| 44 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Advanced Micro Devices |
| 45 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Applied Materials |
| 46 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | Beverly Hills | Live Nation Entertainment |
| 47 | 95051 | 37 | -122 | 61,345 | POINT (-121.98444 37.3483) | California | 2857700 | 2,399,300,000,000 | Santa Clara | Nvidia |
| 48 | 94588 | 38 | -122 | 34,423 | POINT (-121.88178 37.73801) | California | 2857700 | 2,399,300,000,000 | Pleasanton | Workday |
| 49 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | Fremont | TD Synnex |
| 50 | 95035 | 37 | -122 | 78,479 | POINT (-121.87632 37.44319) | California | 2857700 | 2,399,300,000,000 | Milpitas | KLA |
| 51 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | California | 2857700 | 2,399,300,000,000 | Newark | Concentrix |
| 52 | 94568 | 38 | -122 | 70,542 | POINT (-121.90113 37.71596) | California | 2857700 | 2,399,300,000,000 | Dublin | Ross Stores |
| 53 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | Fremont | Lam Research |
| 54 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | Oakland | PG&E |
| 55 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | Oakland | Block |
| 56 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | California | 2857700 | 2,399,300,000,000 | Cupertino | Apple |
| 57 | 95032 | 37 | -122 | 27,682 | POINT (-121.92359 37.20859) | California | 2857700 | 2,399,300,000,000 | Los Gatos | Netflix |
| 58 | 10041 | 41 | -74 | 6,217 | POINT (-74.01 40.7031) | New York | 2825500 | 2,085,200,000,000 | New York | S&P Global |
| 59 | 10105 | 41 | -74 | 0 | POINT (-73.978 40.7644) | New York | 2825500 | 2,085,200,000,000 | New York | Equitable |
| 60 | 10166 | 41 | -74 | 0 | POINT (-73.9769 40.7531) | New York | 2825500 | 2,085,200,000,000 | New York | MetLife |
| 61 | 10285 | 41 | -74 | 0 | POINT (-74.01492 40.71201) | New York | 2825500 | 2,085,200,000,000 | New York | American Express |
| 62 | 10286 | 41 | -74 | 5,269 | POINT (-74.01182 40.7052) | New York | 2825500 | 2,085,200,000,000 | New York | Bank of New York |
| 63 | 14831 | 42 | -77 | 5,986 | POINT (-77.0553 42.1429) | New York | 2825500 | 2,085,200,000,000 | Corning | Corning |
| 64 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | KKR |
| 65 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Pfizer |
| 66 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | New York | 2825500 | 2,085,200,000,000 | Long Island City | Altice USA |
| 67 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Omnicom |
| 68 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | Apollo Global Management |
| 69 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | Loews |
| 70 | 10019 | 41 | -74 | 44,276 | POINT (-73.9853 40.76586) | New York | 2825500 | 2,085,200,000,000 | New York | International Flavors & Fragrances |
| 71 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | 2825500 | 2,085,200,000,000 | New York | American International |
| 72 | 10020 | 41 | -74 | 0 | POINT (-73.98071 40.75917) | New York | 2825500 | 2,085,200,000,000 | New York | Sirius XM |
| 73 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Colgate-Palmolive |
| 74 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Interpublic |
| 75 | 10022 | 41 | -74 | 34,340 | POINT (-73.96787 40.75856) | New York | 2825500 | 2,085,200,000,000 | New York | Jefferies Financial |
| 76 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Verizon |
| 77 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Paramount Global |
| 78 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Marsh & McLennan |
| 79 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Fox |
| 80 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Hess |
| 81 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | News Corp. |
| 82 | 10153 | 41 | -74 | 0 | POINT (-73.97244 40.76362) | New York | 2825500 | 2,085,200,000,000 | New York | Estée Lauder |
| 83 | 10154 | 41 | -74 | 0 | POINT (-73.97249 40.75778) | New York | 2825500 | 2,085,200,000,000 | New York | Blackstone |
| 84 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | 2825500 | 2,085,200,000,000 | New York | StoneX |
| 85 | 10169 | 41 | -74 | 0 | POINT (-73.97643 40.75467) | New York | 2825500 | 2,085,200,000,000 | New York | Voya Financial |
| 86 | 10282 | 41 | -74 | 5,960 | POINT (-74.01495 40.71655) | New York | 2825500 | 2,085,200,000,000 | New York | Goldman Sachs |
| 87 | 10504 | 41 | -74 | 7,853 | POINT (-73.70629 41.13065) | New York | 2825500 | 2,085,200,000,000 | Armonk | IBM |
| 88 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | New York | 2825500 | 2,085,200,000,000 | Purchase | PepsiCo |
| 89 | 10577 | 41 | -74 | 5,901 | POINT (-73.71349 41.03755) | New York | 2825500 | 2,085,200,000,000 | Purchase | Mastercard |
| 90 | 10591 | 41 | -74 | 23,663 | POINT (-73.84653 41.08436) | New York | 2825500 | 2,085,200,000,000 | Tarrytown | Regeneron Pharmaceuticals |
| 91 | 11101 | 41 | -74 | 39,007 | POINT (-73.93916 40.74679) | New York | 2825500 | 2,085,200,000,000 | Long Island City | JetBlue Airways |
| 92 | 11747 | 41 | -73 | 19,826 | POINT (-73.40931 40.78372) | New York | 2825500 | 2,085,200,000,000 | Melville | Henry Schein |
| 93 | 14203 | 43 | -79 | 2,526 | POINT (-78.86507 42.86244) | New York | 2825500 | 2,085,200,000,000 | Buffalo | M&T Bank |
| 94 | 14564 | 43 | -77 | 16,257 | POINT (-77.42417 42.98329) | New York | 2825500 | 2,085,200,000,000 | Victor | Constellation Brands |
| 95 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | PVH |
| 96 | 10036 | 41 | -74 | 30,589 | POINT (-73.99064 40.75976) | New York | 2825500 | 2,085,200,000,000 | New York | Morgan Stanley |
| 97 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Kyndryl s |
| 98 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | TIAA |
| 99 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | JPMorgan Chase |
| 100 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | 2825500 | 2,085,200,000,000 | New York | Oscar Health |
| 101 | 10013 | 41 | -74 | 28,215 | POINT (-74.00472 40.72001) | New York | 2825500 | 2,085,200,000,000 | New York | Citi |
| 102 | 10010 | 41 | -74 | 31,905 | POINT (-73.98243 40.73899) | New York | 2825500 | 2,085,200,000,000 | New York | New York Life Insurance |
| 103 | 10006 | 41 | -74 | 4,475 | POINT (-74.01306 40.70949) | New York | 2825500 | 2,085,200,000,000 | New York | ABM Industries |
| 104 | 10017 | 41 | -74 | 14,985 | POINT (-73.9726 40.75235) | New York | 2825500 | 2,085,200,000,000 | New York | Travelers |
| 105 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Macy's |
| 106 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | BlackRock |
| 107 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Guardian Life |
| 108 | 10001 | 41 | -74 | 29,079 | POINT (-73.99728 40.75064) | New York | 2825500 | 2,085,200,000,000 | New York | Foot Locker |
| 109 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | 2825500 | 2,085,200,000,000 | New York | Warner Bros. Discovery |
| 110 | 10003 | 41 | -74 | 53,825 | POINT (-73.98915 40.73184) | New York | 2825500 | 2,085,200,000,000 | New York | Consolidated Edison |
| 111 | 98134 | 48 | -122 | 779 | POINT (-122.33686 47.57691) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Starbucks |
| 112 | 98188 | 47 | -122 | 26,769 | POINT (-122.27398 47.44754) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Alaska Air |
| 113 | 98390 | 47 | -122 | 11,497 | POINT (-122.22894 47.21195) | Washington | 2750600 | 1,299,400,000,000 | Sumner | Lululemon athletica |
| 114 | 98119 | 48 | -122 | 26,390 | POINT (-122.36932 47.63943) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Expedia |
| 115 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Nordstrom |
| 116 | 98101 | 48 | -122 | 16,396 | POINT (-122.33454 47.61119) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Coupang |
| 117 | 98052 | 48 | -122 | 79,074 | POINT (-122.1203 47.68148) | Washington | 2750600 | 1,299,400,000,000 | Redmond | Microsoft |
| 118 | 98027 | 48 | -122 | 28,335 | POINT (-122.00176 47.50387) | Washington | 2750600 | 1,299,400,000,000 | Issaquah | Costco |
| 119 | 98006 | 48 | -122 | 40,770 | POINT (-122.14957 47.55772) | Washington | 2750600 | 1,299,400,000,000 | Bellevue | Expeditors International of Washington |
| 120 | 98004 | 48 | -122 | 39,435 | POINT (-122.20548 47.61865) | Washington | 2750600 | 1,299,400,000,000 | Bellevue | Paccar |
| 121 | 98109 | 48 | -122 | 32,552 | POINT (-122.34486 47.63128) | Washington | 2750600 | 1,299,400,000,000 | Seattle | Amazon |
| 122 | 75038 | 33 | -97 | 33,097 | POINT (-96.97946 32.87231) | Texas | 2432800 | 2,680,800,000,000 | Irving | Kimberly-Clark |
| 123 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Fluor |
| 124 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Builders FirstSource |
| 125 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Vistra |
| 126 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Caterpillar |
| 127 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | McKesson |
| 128 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Waste Management |
| 129 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Plains GP |
| 130 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | NRG Energy |
| 131 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | EOG Resources |
| 132 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Targa Resources |
| 133 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Commercial Metals |
| 134 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | Irving | Celanese |
| 135 | 75243 | 33 | -97 | 63,907 | POINT (-96.73633 32.91232) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Texas Instruments |
| 136 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | Texas | 2432800 | 2,680,800,000,000 | Plano | Yum China s |
| 137 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | Dallas | CBRE |
| 138 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Jacobs Solutions |
| 139 | 75202 | 33 | -97 | 2,744 | POINT (-96.8037 32.77843) | Texas | 2432800 | 2,680,800,000,000 | Dallas | AT&T |
| 140 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Texas | 2432800 | 2,680,800,000,000 | Dallas | HF Sinclair |
| 141 | 75225 | 33 | -97 | 22,383 | POINT (-96.79109 32.86511) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Energy Transfer |
| 142 | 75235 | 33 | -97 | 19,067 | POINT (-96.84798 32.83219) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Southwest Airlines |
| 143 | 75240 | 33 | -97 | 24,718 | POINT (-96.78924 32.93194) | Texas | 2432800 | 2,680,800,000,000 | Dallas | AECOM |
| 144 | 76155 | 33 | -97 | 6,301 | POINT (-97.04911 32.82404) | Texas | 2432800 | 2,680,800,000,000 | Fort Worth | American Airlines |
| 145 | 76011 | 33 | -97 | 22,297 | POINT (-97.08223 32.7543) | Texas | 2432800 | 2,680,800,000,000 | Arlington | D.R. Horton |
| 146 | 75254 | 33 | -97 | 24,737 | POINT (-96.80127 32.94571) | Texas | 2432800 | 2,680,800,000,000 | Dallas | Tenet Healthcare |
| 147 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Kinder Morgan |
| 148 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Cheniere Energy |
| 149 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Enterprise Products Partners |
| 150 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | CenterPoint Energy |
| 151 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | KBR |
| 152 | 78682 | 30 | -98 | 0 | POINT (-97.7273 30.4076) | Texas | 2432800 | 2,680,800,000,000 | Round Rock | Dell Technologies |
| 153 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | Texas | 2432800 | 2,680,800,000,000 | San Antonio | USAA |
| 154 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | Houston | Chevron |
| 155 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Texas | 2432800 | 2,680,800,000,000 | Midland | Diamondback Energy |
| 156 | 78741 | 30 | -98 | 45,274 | POINT (-97.71389 30.23007) | Texas | 2432800 | 2,680,800,000,000 | Austin | Oracle |
| 157 | 78725 | 30 | -98 | 10,810 | POINT (-97.60859 30.23554) | Texas | 2432800 | 2,680,800,000,000 | Austin | Tesla |
| 158 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Texas | 2432800 | 2,680,800,000,000 | San Antonio | Valero Energy |
| 159 | 78130 | 30 | -98 | 95,787 | POINT (-98.06877 29.69224) | Texas | 2432800 | 2,680,800,000,000 | New Braunfels | Rush Enterprises |
| 160 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | Spring | Hewlett Packard |
| 161 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | Spring | Exxon Mobil |
| 162 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | Houston | Baker Hughes |
| 163 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | Houston | ConocoPhillips |
| 164 | 77077 | 30 | -96 | 63,421 | POINT (-95.64189 29.75375) | Texas | 2432800 | 2,680,800,000,000 | Houston | Sysco |
| 165 | 77056 | 30 | -95 | 23,314 | POINT (-95.46806 29.74849) | Texas | 2432800 | 2,680,800,000,000 | Houston | Westlake |
| 166 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Texas | 2432800 | 2,680,800,000,000 | Houston | Occidental Petroleum |
| 167 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | NOV |
| 168 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | APA |
| 169 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | Houston | Phillips 66 |
| 170 | 77032 | 30 | -95 | 13,536 | POINT (-95.34004 29.96523) | Texas | 2432800 | 2,680,800,000,000 | Houston | Halliburton |
| 171 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | Houston | Par Pacific |
| 172 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | Houston | 1 Automotive |
| 173 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Texas | 2432800 | 2,680,800,000,000 | Houston | Corebridge Financial |
| 174 | 77008 | 30 | -95 | 40,155 | POINT (-95.41766 29.79856) | Texas | 2432800 | 2,680,800,000,000 | Houston | Quanta Services |
| 175 | 76262 | 33 | -97 | 43,589 | POINT (-97.22101 33.01137) | Texas | 2432800 | 2,680,800,000,000 | Westlake | Charles Schwab |
| 176 | 72762 | 36 | -94 | 47,402 | POINT (-94.22794 36.18747) | Arkansas | 2283200 | 764,300,000,000 | Springdale | Tyson Foods |
| 177 | 72745 | 36 | -94 | 14,521 | POINT (-94.10046 36.2477) | Arkansas | 2283200 | 764,300,000,000 | Lowell | J.B. Hunt Transport Services |
| 178 | 72712 | 36 | -94 | 38,072 | POINT (-94.22196 36.39837) | Arkansas | 2283200 | 764,300,000,000 | Bentonville | Walmart |
| 179 | 71730 | 33 | -93 | 29,187 | POINT (-92.63458 33.20303) | Arkansas | 2283200 | 764,300,000,000 | El Dorado | Murphy USA |
| 180 | 61710 | 41 | -89 | 79,633 | POINT (-88.9894 40.516) | Illinois | 1655400 | 1,040,200,000,000 | Bloomington | State Farm |
| 181 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Mondelez |
| 182 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | Illinois | 1655400 | 1,040,200,000,000 | Abbott Park | Abbott Laboratories |
| 183 | 60523 | 42 | -88 | 10,012 | POINT (-87.95406 41.83713) | Illinois | 1655400 | 1,040,200,000,000 | Oak Brook | Ace Hardware |
| 184 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Deerfield | Walgreens |
| 185 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Riverwoods | Discover Financial |
| 186 | 60015 | 42 | -88 | 27,720 | POINT (-87.87486 42.17239) | Illinois | 1655400 | 1,040,200,000,000 | Deerfield | Baxter International |
| 187 | 60018 | 42 | -88 | 29,302 | POINT (-87.89846 41.99629) | Illinois | 1655400 | 1,040,200,000,000 | Rosemont | US Foods |
| 188 | 60025 | 42 | -88 | 40,877 | POINT (-87.81204 42.07466) | Illinois | 1655400 | 1,040,200,000,000 | Glenview | Illinois Tool Works |
| 189 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Illinois | 1655400 | 1,040,200,000,000 | Lake Forest | W.W. Grainger |
| 190 | 60045 | 42 | -88 | 20,957 | POINT (-87.87006 42.23807) | Illinois | 1655400 | 1,040,200,000,000 | Lake Forest | Packaging Corp. of America |
| 191 | 60061 | 42 | -88 | 27,883 | POINT (-87.96046 42.2334) | Illinois | 1655400 | 1,040,200,000,000 | Vernon Hills | CDW |
| 192 | 60062 | 42 | -88 | 41,667 | POINT (-87.84235 42.12663) | Illinois | 1655400 | 1,040,200,000,000 | Northbrook | Allstate |
| 193 | 60064 | 42 | -88 | 15,047 | POINT (-87.86122 42.3237) | Illinois | 1655400 | 1,040,200,000,000 | North Chicago | AbbVie |
| 194 | 60154 | 42 | -88 | 16,524 | POINT (-87.88986 41.84923) | Illinois | 1655400 | 1,040,200,000,000 | Westchester | Ingredion |
| 195 | 60440 | 42 | -88 | 52,074 | POINT (-88.07572 41.70125) | Illinois | 1655400 | 1,040,200,000,000 | Bolingbrook | Ulta Beauty |
| 196 | 60008 | 42 | -88 | 22,949 | POINT (-88.0229 42.0739) | Illinois | 1655400 | 1,040,200,000,000 | Rolling Meadows | Arthur J. Gallagher |
| 197 | 60515 | 42 | -88 | 29,045 | POINT (-88.0247 41.80991) | Illinois | 1655400 | 1,040,200,000,000 | Downers Grove | Dover |
| 198 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Archer Daniels Midland |
| 199 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Molson Coors Beverage |
| 200 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Motorola Solutions |
| 201 | 60661 | 42 | -88 | 11,516 | POINT (-87.64409 41.88291) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | GE HealthCare Technologies |
| 202 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Conagra Brands |
| 203 | 60654 | 42 | -88 | 24,303 | POINT (-87.63673 41.89209) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Kellanova |
| 204 | 60607 | 42 | -88 | 30,197 | POINT (-87.65175 41.87467) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | McDonald's |
| 205 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Kraft Heinz |
| 206 | 61265 | 41 | -90 | 43,851 | POINT (-90.48895 41.48195) | Illinois | 1655400 | 1,040,200,000,000 | Moline | Deere |
| 207 | 60606 | 42 | -88 | 3,527 | POINT (-87.63724 41.88178) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | United Airlines |
| 208 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Northern Trust |
| 209 | 60603 | 42 | -88 | 1,126 | POINT (-87.6274 41.88018) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Exelon |
| 210 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Old Republic International |
| 211 | 60601 | 42 | -88 | 16,292 | POINT (-87.62197 41.88527) | Illinois | 1655400 | 1,040,200,000,000 | Chicago | Jones Lang LaSalle |
| 212 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | General Dynamics |
| 213 | 20170 | 39 | -77 | 43,372 | POINT (-77.38042 38.98075) | Virginia | 1461200 | 738,400,000,000 | Herndon | QXO Building Products |
| 214 | 20147 | 39 | -77 | 67,007 | POINT (-77.47958 39.04151) | Virginia | 1461200 | 738,400,000,000 | Ashburn | DXC Technology |
| 215 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | Leidos s |
| 216 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Virginia | 1461200 | 738,400,000,000 | Richmond | Performance Food |
| 217 | 23607 | 37 | -76 | 23,028 | POINT (-76.42235 36.98753) | Virginia | 1461200 | 738,400,000,000 | Newport News | Huntington Ingalls Industries |
| 218 | 23606 | 37 | -76 | 29,899 | POINT (-76.49557 37.07847) | Virginia | 1461200 | 738,400,000,000 | Newport News | Ferguson |
| 219 | 23320 | 37 | -76 | 59,626 | POINT (-76.21807 36.75208) | Virginia | 1461200 | 738,400,000,000 | Chesapeake | Dollar Tree |
| 220 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | CACI International |
| 221 | 23238 | 38 | -78 | 25,893 | POINT (-77.64138 37.59595) | Virginia | 1461200 | 738,400,000,000 | Richmond | CarMax |
| 222 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | NVR |
| 223 | 23230 | 38 | -77 | 8,304 | POINT (-77.49153 37.587) | Virginia | 1461200 | 738,400,000,000 | Richmond | Altria |
| 224 | 20190 | 39 | -77 | 22,092 | POINT (-77.33806 38.95968) | Virginia | 1461200 | 738,400,000,000 | Reston | Science Applications International |
| 225 | 22203 | 39 | -77 | 25,921 | POINT (-77.1164 38.87377) | Virginia | 1461200 | 738,400,000,000 | Arlington | AES |
| 226 | 22042 | 39 | -77 | 34,631 | POINT (-77.19406 38.86463) | Virginia | 1461200 | 738,400,000,000 | Falls Church | Northrop Grumman |
| 227 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Virginia | 1461200 | 738,400,000,000 | Glen Allen | Markel |
| 228 | 23060 | 38 | -78 | 36,111 | POINT (-77.53427 37.65981) | Virginia | 1461200 | 738,400,000,000 | Glen Allen | Owens & Minor |
| 229 | 23219 | 38 | -77 | 3,856 | POINT (-77.43484 37.54076) | Virginia | 1461200 | 738,400,000,000 | Richmond | Dominion Energy |
| 230 | 23227 | 38 | -77 | 25,574 | POINT (-77.44234 37.61486) | Virginia | 1461200 | 738,400,000,000 | Richmond | ARKO |
| 231 | 22209 | 39 | -77 | 13,725 | POINT (-77.07309 38.89413) | Virginia | 1461200 | 738,400,000,000 | Arlington | RTX |
| 232 | 22202 | 39 | -77 | 27,352 | POINT (-77.05175 38.8569) | Virginia | 1461200 | 738,400,000,000 | Arlington | Boeing |
| 233 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Hilton |
| 234 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Capital One |
| 235 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Freddie Mac |
| 236 | 22102 | 39 | -77 | 28,577 | POINT (-77.22901 38.95199) | Virginia | 1461200 | 738,400,000,000 | McLean | Booz Allen Hamilton |
| 237 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Global Payments |
| 238 | 30354 | 34 | -84 | 15,487 | POINT (-84.38609 33.66058) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Delta Airlines |
| 239 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Assurant |
| 240 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Genuine Parts |
| 241 | 30339 | 34 | -84 | 34,872 | POINT (-84.46483 33.86786) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Home Depot |
| 242 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Newell Brands |
| 243 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Graphic Packaging |
| 244 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Intercontinental Exchange |
| 245 | 30328 | 34 | -84 | 38,821 | POINT (-84.38617 33.93194) | Georgia | 1327300 | 548,300,000,000 | Atlanta | UPS |
| 246 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Norfolk Southern |
| 247 | 30326 | 34 | -84 | 8,497 | POINT (-84.36342 33.84957) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Pulte |
| 248 | 30313 | 34 | -84 | 10,845 | POINT (-84.39761 33.76369) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Coca-Cola |
| 249 | 30308 | 34 | -84 | 23,329 | POINT (-84.37773 33.77094) | Georgia | 1327300 | 548,300,000,000 | Atlanta | Southern |
| 250 | 30097 | 34 | -84 | 45,543 | POINT (-84.14702 34.0271) | Georgia | 1327300 | 548,300,000,000 | Duluth | Asbury Automotive |
| 251 | 30096 | 34 | -84 | 71,141 | POINT (-84.14791 33.97691) | Georgia | 1327300 | 548,300,000,000 | Duluth | AGCO |
| 252 | 31999 | 32 | -85 | 3,469 | POINT (-84.98772 32.46078) | Georgia | 1327300 | 548,300,000,000 | Columbus | Aflac |
| 253 | 30701 | 34 | -85 | 43,078 | POINT (-84.95385 34.49535) | Georgia | 1327300 | 548,300,000,000 | Calhoun | Mohawk Industries |
| 254 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | 3M |
| 255 | 55144 | 45 | -93 | 11,636 | POINT (-93.04758 44.92912) | Minnesota | 1269900 | 802,600,000,000 | Maplewood | Solventum |
| 256 | 55474 | 45 | -93 | 28,071 | POINT (-93.27 44.98) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Ameriprise Financial |
| 257 | 55347 | 45 | -93 | 30,467 | POINT (-93.46638 44.82931) | Minnesota | 1269900 | 802,600,000,000 | Eden Prairie | C.H. Robinson Worldwide |
| 258 | 55077 | 45 | -93 | 14,585 | POINT (-93.07574 44.81989) | Minnesota | 1269900 | 802,600,000,000 | Inver Grove Heights | CHS |
| 259 | 55402 | 45 | -93 | 760 | POINT (-93.27119 44.97608) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | U.S. Bancorp |
| 260 | 55987 | 44 | -92 | 33,911 | POINT (-91.63143 43.98469) | Minnesota | 1269900 | 802,600,000,000 | Winona | Fastenal |
| 261 | 55912 | 44 | -93 | 29,438 | POINT (-92.99148 43.6827) | Minnesota | 1269900 | 802,600,000,000 | Austin | Hormel Foods |
| 262 | 55426 | 45 | -93 | 25,451 | POINT (-93.38139 44.95635) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | General Mills |
| 263 | 55423 | 45 | -93 | 36,779 | POINT (-93.28144 44.87663) | Minnesota | 1269900 | 802,600,000,000 | Richfield | Best Buy |
| 264 | 55415 | 45 | -93 | 6,474 | POINT (-93.2578 44.97463) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Thrivent Financial for Lutherans |
| 265 | 55403 | 45 | -93 | 17,354 | POINT (-93.28588 44.97023) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Target |
| 266 | 55101 | 45 | -93 | 7,937 | POINT (-93.08739 44.95111) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | Securian Financial |
| 267 | 55102 | 45 | -93 | 19,565 | POINT (-93.12149 44.93216) | Minnesota | 1269900 | 802,600,000,000 | St. Paul | Ecolab |
| 268 | 55126 | 45 | -93 | 27,484 | POINT (-93.13581 45.08614) | Minnesota | 1269900 | 802,600,000,000 | Arden Hills | Land O'Lakes |
| 269 | 55344 | 45 | -93 | 14,180 | POINT (-93.43037 44.86452) | Minnesota | 1269900 | 802,600,000,000 | Eden Prairie | UnitedHealth |
| 270 | 55401 | 45 | -93 | 11,526 | POINT (-93.26984 44.98526) | Minnesota | 1269900 | 802,600,000,000 | Minneapolis | Xcel Energy |
| 271 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Sherwin-Williams |
| 272 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | Huntington Bancshares |
| 273 | 43659 | 42 | -84 | 0 | POINT (-83.5554 41.6639) | Ohio | 1255100 | 1,035,800,000,000 | Toledo | Owens Corning |
| 274 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Ohio | 1255100 | 1,035,800,000,000 | Findlay | Marathon Petroleum |
| 275 | 45262 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Cintas |
| 276 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Fifth Third Bancorp |
| 277 | 44316 | 41 | -81 | 0 | POINT (-81.47083 41.07854) | Ohio | 1255100 | 1,035,800,000,000 | Akron | Goodyear Tire & Rubber |
| 278 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | Ohio | 1255100 | 1,035,800,000,000 | Evendale | General Electric |
| 279 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | KeyCorp |
| 280 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | American Financial |
| 281 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Cleveland-Cliffs |
| 282 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | TransDigm |
| 283 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | Ohio | 1255100 | 1,035,800,000,000 | Toledo | Welltower |
| 284 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | Maumee | Dana |
| 285 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | Maumee | Andersons |
| 286 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | American Electric Power |
| 287 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | Columbus | Nationwide |
| 288 | 43082 | 40 | -83 | 33,799 | POINT (-82.88437 40.15537) | Ohio | 1255100 | 1,035,800,000,000 | Westerville | Vertiv s |
| 289 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Ohio | 1255100 | 1,035,800,000,000 | Dublin | Cardinal Health |
| 290 | 44124 | 41 | -81 | 40,046 | POINT (-81.46774 41.49999) | Ohio | 1255100 | 1,035,800,000,000 | Cleveland | Parker-Hannifin |
| 291 | 44143 | 42 | -81 | 24,337 | POINT (-81.47513 41.55358) | Ohio | 1255100 | 1,035,800,000,000 | Mayfield Village | Progressive |
| 292 | 44308 | 41 | -82 | 1,261 | POINT (-81.51751 41.0818) | Ohio | 1255100 | 1,035,800,000,000 | Akron | FirstEnergy |
| 293 | 44667 | 41 | -82 | 13,688 | POINT (-81.76495 40.83386) | Ohio | 1255100 | 1,035,800,000,000 | Orrville | J.M. Smucker |
| 294 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | Ohio | 1255100 | 1,035,800,000,000 | Fairfield | Cincinnati Financial |
| 295 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Kroger |
| 296 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Procter & Gamble |
| 297 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | Cincinnati | Western & Southern Financial |
| 298 | 44060 | 42 | -81 | 60,257 | POINT (-81.32806 41.67742) | Ohio | 1255100 | 1,035,800,000,000 | Mentor | Avery Dennison |
In [145]:
musmaxempst10 = gdfstsusmaxempst10.explore(column='Employees', name='The Biggest Employer State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempst10.explore(m=musmaxempst10, column='Employees', name='The Biggest Employer State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempst10)
musmaxempst10
Out[145]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [146]:
# The Most Efficient City in US
dfusmaxeffct = df.groupby(['State','City'], as_index=False).sum('Employees')
dfusmaxeffct.insert(4,'Efficiency',1)
dfusmaxeffct['Efficiency'] = dfusmaxeffct['Revenue (rounded)'] / dfusmaxeffct['Employees']
dfusmaxeffct = dfusmaxeffct.sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfusmaxeffct10 = dfusmaxeffct.head(10)
dfusmaxeffct
Out[146]:
| State | City | Employees | Revenue (rounded) | Efficiency | |
|---|---|---|---|---|---|
| 0 | California | El Segundo | 500 | 9,700,000,000 | 19,400,000 |
| 1 | Ohio | Findlay | 18300 | 140,400,000,000 | 7,672,131 |
| 2 | Oklahoma | Oklahoma City | 2300 | 15,900,000,000 | 6,913,043 |
| 3 | Pennsylvania | Conshohocken | 44000 | 294,000,000,000 | 6,681,818 |
| 4 | Texas | Midland | 2000 | 11,100,000,000 | 5,550,000 |
| 5 | Missouri | Chesterfield | 4100 | 22,100,000,000 | 5,390,244 |
| 6 | Ohio | Dublin | 48400 | 226,800,000,000 | 4,685,950 |
| 7 | Minnesota | Inver Grove Heights | 10700 | 39,300,000,000 | 3,672,897 |
| 8 | Texas | San Antonio | 47900 | 172,600,000,000 | 3,603,340 |
| 9 | Connecticut | Bloomfield | 72400 | 247,100,000,000 | 3,412,983 |
| 10 | Florida | Miami | 25300 | 85,200,000,000 | 3,367,589 |
| 11 | Texas | Spring | 121900 | 379,700,000,000 | 3,114,848 |
| 12 | Oklahoma | Tulsa | 11000 | 32,200,000,000 | 2,927,273 |
| 13 | California | Los Gatos | 14000 | 39,000,000,000 | 2,785,714 |
| 14 | Massachusetts | Springfield | 21900 | 55,000,000,000 | 2,511,416 |
| 15 | Texas | Arlington | 14800 | 36,800,000,000 | 2,486,486 |
| 16 | California | Cupertino | 164000 | 391,000,000,000 | 2,384,146 |
| 17 | California | Long Beach | 18000 | 40,600,000,000 | 2,255,556 |
| 18 | California | Menlo Park | 74100 | 164,500,000,000 | 2,219,973 |
| 19 | Pennsylvania | Fort Washington | 4900 | 10,800,000,000 | 2,204,082 |
| 20 | Michigan | Lansing | 7300 | 15,800,000,000 | 2,164,384 |
| 21 | Ohio | Fairfield | 5600 | 11,300,000,000 | 2,017,857 |
| 22 | District of Columbia | Washington | 93200 | 185,200,000,000 | 1,987,124 |
| 23 | Pennsylvania | Erie | 6700 | 13,200,000,000 | 1,970,149 |
| 24 | Wisconsin | Madison | 11100 | 21,300,000,000 | 1,918,919 |
| 25 | Pennsylvania | Radnor | 9800 | 18,400,000,000 | 1,877,551 |
| 26 | California | Irvine | 26100 | 48,000,000,000 | 1,839,080 |
| 27 | Illinois | Bloomington | 67400 | 123,000,000,000 | 1,824,926 |
| 28 | Minnesota | Arden Hills | 9000 | 16,200,000,000 | 1,800,000 |
| 29 | Rhode Island | Johnston | 5800 | 10,400,000,000 | 1,793,103 |
| 30 | California | Mountain View | 207500 | 366,300,000,000 | 1,765,301 |
| 31 | California | Fremont | 43200 | 73,400,000,000 | 1,699,074 |
| 32 | Maryland | Baltimore | 14200 | 23,600,000,000 | 1,661,972 |
| 33 | California | Foster City | 17600 | 28,800,000,000 | 1,636,364 |
| 34 | Texas | Houston | 557600 | 906,500,000,000 | 1,625,717 |
| 35 | Texas | Irving | 287000 | 462,000,000,000 | 1,609,756 |
| 36 | New Jersey | Newark | 50900 | 80,700,000,000 | 1,585,462 |
| 37 | California | Woodland Hills | 9900 | 15,500,000,000 | 1,565,657 |
| 38 | Arkansas | El Dorado | 11600 | 17,900,000,000 | 1,543,103 |
| 39 | Ohio | Columbus | 58700 | 90,300,000,000 | 1,538,330 |
| 40 | Georgia | Columbus | 12700 | 18,900,000,000 | 1,488,189 |
| 41 | Florida | Juno Beach | 16800 | 24,800,000,000 | 1,476,190 |
| 42 | Rhode Island | Woonsocket | 259500 | 372,800,000,000 | 1,436,609 |
| 43 | New Jersey | Parsippany | 38200 | 54,200,000,000 | 1,418,848 |
| 44 | New Jersey | Princeton | 34100 | 48,300,000,000 | 1,416,422 |
| 45 | Illinois | Vernon Hills | 15100 | 21,000,000,000 | 1,390,728 |
| 46 | Connecticut | Hartford | 19100 | 26,500,000,000 | 1,387,435 |
| 47 | Indiana | Indianapolis | 172700 | 238,900,000,000 | 1,383,324 |
| 48 | Indiana | Fort Wayne | 13000 | 17,500,000,000 | 1,346,154 |
| 49 | Colorado | Centennial | 21500 | 27,900,000,000 | 1,297,674 |
| 50 | Missouri | St. Louis | 160700 | 207,500,000,000 | 1,291,226 |
| 51 | Virginia | Richmond | 99300 | 127,000,000,000 | 1,278,953 |
| 52 | Illinois | Rosemont | 30000 | 37,900,000,000 | 1,263,333 |
| 53 | California | Rosemead | 14000 | 17,600,000,000 | 1,257,143 |
| 54 | California | Corona | 6000 | 7,500,000,000 | 1,250,000 |
| 55 | California | Oakland | 39800 | 48,500,000,000 | 1,218,593 |
| 56 | Oregon | Medford | 30200 | 36,600,000,000 | 1,211,921 |
| 57 | Virginia | Herndon | 8100 | 9,800,000,000 | 1,209,877 |
| 58 | Michigan | Midland | 36000 | 43,000,000,000 | 1,194,444 |
| 59 | California | Thousand Oaks | 28000 | 33,400,000,000 | 1,192,857 |
| 60 | Michigan | Detroit | 182200 | 216,300,000,000 | 1,187,157 |
| 61 | Tennessee | Chattanooga | 10900 | 12,900,000,000 | 1,183,486 |
| 62 | Illinois | Northbrook | 55200 | 64,100,000,000 | 1,161,232 |
| 63 | Arizona | Scottsdale | 19000 | 22,000,000,000 | 1,157,895 |
| 64 | Ohio | Mayfield Village | 66300 | 75,400,000,000 | 1,137,255 |
| 65 | Illinois | Riverwoods | 21000 | 23,600,000,000 | 1,123,810 |
| 66 | California | Palo Alto | 95000 | 106,000,000,000 | 1,115,789 |
| 67 | Michigan | Dearborn | 171000 | 185,000,000,000 | 1,081,871 |
| 68 | New York | Victor | 9300 | 10,000,000,000 | 1,075,269 |
| 69 | Washington | Redmond | 228000 | 245,100,000,000 | 1,075,000 |
| 70 | Florida | Fort Lauderdale | 25100 | 26,800,000,000 | 1,067,729 |
| 71 | Michigan | Bloomfield Hills | 28900 | 30,500,000,000 | 1,055,363 |
| 72 | Illinois | North Chicago | 55000 | 56,300,000,000 | 1,023,636 |
| 73 | California | Santa Clara | 250200 | 255,600,000,000 | 1,021,583 |
| 74 | Kentucky | Louisville | 134400 | 136,600,000,000 | 1,016,369 |
| 75 | Minnesota | Eden Prairie | 413800 | 418,000,000,000 | 1,010,150 |
| 76 | Texas | New Braunfels | 7900 | 7,800,000,000 | 987,342 |
| 77 | Louisiana | New Orleans | 12300 | 11,900,000,000 | 967,480 |
| 78 | New York | Tarrytown | 15100 | 14,200,000,000 | 940,397 |
| 79 | Illinois | Moline | 55500 | 51,700,000,000 | 931,532 |
| 80 | Nebraska | Omaha | 463100 | 427,000,000,000 | 922,047 |
| 81 | Massachusetts | Boston | 115500 | 106,400,000,000 | 921,212 |
| 82 | Ohio | Orrville | 9000 | 8,200,000,000 | 911,111 |
| 83 | Wisconsin | Milwaukee | 106900 | 96,700,000,000 | 904,584 |
| 84 | Washington | Bellevue | 49000 | 44,300,000,000 | 904,082 |
| 85 | Michigan | Jackson | 8300 | 7,500,000,000 | 903,614 |
| 86 | California | Beverly Hills | 34200 | 30,700,000,000 | 897,661 |
| 87 | New York | New York | 2028200 | 1,820,500,000,000 | 897,594 |
| 88 | Texas | Round Rock | 108000 | 95,600,000,000 | 885,185 |
| 89 | New Jersey | Rahway | 74000 | 64,200,000,000 | 867,568 |
| 90 | California | San Diego | 74800 | 64,600,000,000 | 863,636 |
| 91 | California | San Mateo | 10200 | 8,500,000,000 | 833,333 |
| 92 | Iowa | Des Moines | 19700 | 16,100,000,000 | 817,259 |
| 93 | Texas | Westlake | 32100 | 26,000,000,000 | 809,969 |
| 94 | Colorado | Englewood | 32700 | 25,800,000,000 | 788,991 |
| 95 | Arizona | Tempe | 17400 | 13,700,000,000 | 787,356 |
| 96 | North Carolina | Charlotte | 422700 | 331,300,000,000 | 783,771 |
| 97 | Washington | Issaquah | 333000 | 254,500,000,000 | 764,264 |
| 98 | Illinois | Oak Brook | 12500 | 9,500,000,000 | 760,000 |
| 99 | Colorado | Westminster | 16000 | 12,100,000,000 | 756,250 |
| 100 | Georgia | Duluth | 39000 | 28,900,000,000 | 741,026 |
| 101 | Ohio | Toledo | 25700 | 19,000,000,000 | 739,300 |
| 102 | Ohio | Evendale | 53000 | 38,700,000,000 | 730,189 |
| 103 | Rhode Island | Providence | 79600 | 57,100,000,000 | 717,337 |
| 104 | Virginia | McLean | 275900 | 197,900,000,000 | 717,289 |
| 105 | Pennsylvania | Allentown | 29100 | 20,600,000,000 | 707,904 |
| 106 | New Jersey | Summit | 22000 | 15,500,000,000 | 704,545 |
| 107 | Tennessee | Kingsport | 14000 | 9,400,000,000 | 671,429 |
| 108 | Tennessee | Brentwood | 41000 | 27,400,000,000 | 668,293 |
| 109 | New Jersey | Camden | 14400 | 9,600,000,000 | 666,667 |
| 110 | Florida | Sunny Isles Beach | 15000 | 10,000,000,000 | 666,667 |
| 111 | Florida | Plantation | 18000 | 11,900,000,000 | 661,111 |
| 112 | Illinois | Westchester | 11200 | 7,400,000,000 | 660,714 |
| 113 | Kansas | Merriam | 14000 | 9,100,000,000 | 650,000 |
| 114 | California | Milpitas | 15100 | 9,800,000,000 | 649,007 |
| 115 | Oregon | Beaverton | 79400 | 51,400,000,000 | 647,355 |
| 116 | New Jersey | New Brunswick | 138100 | 88,800,000,000 | 643,012 |
| 117 | Illinois | Lake Forest | 40400 | 25,600,000,000 | 633,663 |
| 118 | Michigan | Byron Center | 15000 | 9,500,000,000 | 633,333 |
| 119 | Florida | Jacksonville | 114900 | 71,700,000,000 | 624,021 |
| 120 | Florida | Tampa | 36800 | 22,900,000,000 | 622,283 |
| 121 | Texas | Dallas | 590100 | 366,500,000,000 | 621,081 |
| 122 | California | San Jose | 248200 | 153,000,000,000 | 616,438 |
| 123 | New York | Buffalo | 22100 | 13,500,000,000 | 610,860 |
| 124 | Virginia | Glen Allen | 45200 | 27,300,000,000 | 603,982 |
| 125 | Arizona | Phoenix | 121000 | 73,000,000,000 | 603,306 |
| 126 | California | San Francisco | 492000 | 296,000,000,000 | 601,626 |
| 127 | California | Redwood City | 27300 | 16,300,000,000 | 597,070 |
| 128 | New York | Long Island City | 30700 | 18,300,000,000 | 596,091 |
| 129 | California | Manhattan Beach | 15100 | 9,000,000,000 | 596,026 |
| 130 | Minnesota | Austin | 20000 | 11,900,000,000 | 595,000 |
| 131 | Connecticut | Norwalk | 64600 | 38,300,000,000 | 592,879 |
| 132 | Connecticut | Stamford | 225500 | 132,500,000,000 | 587,583 |
| 133 | Pennsylvania | Hershey | 19300 | 11,200,000,000 | 580,311 |
| 134 | Wisconsin | Oshkosh | 18500 | 10,700,000,000 | 578,378 |
| 135 | Pennsylvania | Pittsburgh | 209800 | 119,200,000,000 | 568,160 |
| 136 | Illinois | Deerfield | 290500 | 162,800,000,000 | 560,413 |
| 137 | California | Sunnyvale | 15600 | 8,400,000,000 | 538,462 |
| 138 | Alabama | Birmingham | 31600 | 16,800,000,000 | 531,646 |
| 139 | Texas | Austin | 284700 | 150,700,000,000 | 529,329 |
| 140 | Massachusetts | Cambridge | 84400 | 44,600,000,000 | 528,436 |
| 141 | Louisiana | Monroe | 25000 | 13,100,000,000 | 524,000 |
| 142 | Massachusetts | Burlington | 29400 | 15,400,000,000 | 523,810 |
| 143 | Virginia | Newport News | 79000 | 41,100,000,000 | 520,253 |
| 144 | Florida | Palm Beach Gardens | 48000 | 24,800,000,000 | 516,667 |
| 145 | Delaware | Wilmington | 24000 | 12,400,000,000 | 516,667 |
| 146 | Ohio | Maumee | 41900 | 21,600,000,000 | 515,513 |
| 147 | Illinois | Chicago | 724600 | 368,100,000,000 | 508,004 |
| 148 | New York | Melville | 25000 | 12,700,000,000 | 508,000 |
| 149 | Indiana | Columbus | 69600 | 34,100,000,000 | 489,943 |
| 150 | Minnesota | Richfield | 85000 | 41,500,000,000 | 488,235 |
| 151 | Massachusetts | Waltham | 128800 | 60,100,000,000 | 466,615 |
| 152 | Ohio | Cincinnati | 593500 | 276,100,000,000 | 465,206 |
| 153 | Pennsylvania | Canonsburg | 32000 | 14,700,000,000 | 459,375 |
| 154 | Florida | Melbourne | 47000 | 21,300,000,000 | 453,191 |
| 155 | Indiana | Warsaw | 17000 | 7,700,000,000 | 452,941 |
| 156 | Iowa | Ankeny | 33100 | 14,900,000,000 | 450,151 |
| 157 | Indiana | Elkhart | 22300 | 10,000,000,000 | 448,430 |
| 158 | California | Burbank | 205000 | 91,400,000,000 | 445,854 |
| 159 | Arizona | Chandler | 36600 | 16,300,000,000 | 445,355 |
| 160 | Virginia | Arlington | 367100 | 159,500,000,000 | 434,487 |
| 161 | Michigan | Livonia | 18000 | 7,800,000,000 | 433,333 |
| 162 | Massachusetts | Marlborough | 86000 | 37,200,000,000 | 432,558 |
| 163 | Michigan | Portage | 53000 | 22,600,000,000 | 426,415 |
| 164 | Idaho | Boise | 244600 | 104,300,000,000 | 426,410 |
| 165 | Virginia | Falls Church | 97000 | 41,000,000,000 | 422,680 |
| 166 | Minnesota | St. Paul | 115100 | 48,500,000,000 | 421,373 |
| 167 | Ohio | Cleveland | 188400 | 79,300,000,000 | 420,913 |
| 168 | Colorado | Denver | 123800 | 51,200,000,000 | 413,570 |
| 169 | Virginia | Reston | 220000 | 90,300,000,000 | 410,455 |
| 170 | California | Pleasanton | 20500 | 8,400,000,000 | 409,756 |
| 171 | Texas | Fort Worth | 133300 | 54,200,000,000 | 406,602 |
| 172 | Ohio | Akron | 80300 | 31,900,000,000 | 397,260 |
| 173 | Georgia | Atlanta | 1233700 | 489,700,000,000 | 396,936 |
| 174 | North Carolina | Raleigh | 65300 | 25,900,000,000 | 396,631 |
| 175 | Massachusetts | Wilmington | 24000 | 9,400,000,000 | 391,667 |
| 176 | North Carolina | Mooresville | 215500 | 83,700,000,000 | 388,399 |
| 177 | Arkansas | Springdale | 138000 | 53,300,000,000 | 386,232 |
| 178 | Michigan | Benton Harbor | 44000 | 16,600,000,000 | 377,273 |
| 179 | Minnesota | Maplewood | 22000 | 8,300,000,000 | 377,273 |
| 180 | Minnesota | Minneapolis | 573300 | 211,400,000,000 | 368,742 |
| 181 | Illinois | Abbott Park | 114000 | 42,000,000,000 | 368,421 |
| 182 | Illinois | Glenview | 44000 | 15,900,000,000 | 361,364 |
| 183 | Arkansas | Lowell | 33600 | 12,100,000,000 | 360,119 |
| 184 | Pennsylvania | Coraopolis | 37400 | 13,400,000,000 | 358,289 |
| 185 | Minnesota | Winona | 21000 | 7,500,000,000 | 357,143 |
| 186 | Washington | Seattle | 2101600 | 744,900,000,000 | 354,444 |
| 187 | Illinois | Downers Grove | 24000 | 8,400,000,000 | 350,000 |
| 188 | Maryland | Bethesda | 276000 | 96,100,000,000 | 348,188 |
| 189 | Florida | Estero | 26000 | 9,000,000,000 | 346,154 |
| 190 | New York | Purchase | 354300 | 120,100,000,000 | 338,978 |
| 191 | Arkansas | Bentonville | 2100000 | 681,000,000,000 | 324,286 |
| 192 | Connecticut | New Britain | 48500 | 15,400,000,000 | 317,526 |
| 193 | Pennsylvania | Philadelphia | 448700 | 141,100,000,000 | 314,464 |
| 194 | Tennessee | Antioch | 47000 | 14,400,000,000 | 306,383 |
| 195 | Florida | Coral Gables | 82700 | 24,900,000,000 | 301,088 |
| 196 | New Jersey | Roseland | 64000 | 19,200,000,000 | 300,000 |
| 197 | Missouri | Des Peres | 55000 | 16,300,000,000 | 296,364 |
| 198 | Indiana | Evansville | 42000 | 12,300,000,000 | 292,857 |
| 199 | Illinois | Bolingbrook | 39000 | 11,300,000,000 | 289,744 |
| 200 | Florida | St. Petersburg | 157000 | 43,800,000,000 | 278,981 |
| 201 | New Jersey | Franklin Lakes | 74000 | 20,200,000,000 | 272,973 |
| 202 | Washington | Sumner | 39000 | 10,600,000,000 | 271,795 |
| 203 | Wisconsin | Menomonee Falls | 60000 | 16,200,000,000 | 270,000 |
| 204 | Nevada | Las Vegas | 109100 | 28,500,000,000 | 261,228 |
| 205 | Tennessee | Nashville | 271000 | 70,600,000,000 | 260,517 |
| 206 | Ohio | Westerville | 31000 | 8,000,000,000 | 258,065 |
| 207 | Georgia | Calhoun | 41900 | 10,800,000,000 | 257,757 |
| 208 | Ohio | Mentor | 35000 | 8,800,000,000 | 251,429 |
| 209 | Michigan | Auburn Hills | 100600 | 24,500,000,000 | 243,539 |
| 210 | Tennessee | Franklin | 52500 | 12,600,000,000 | 240,000 |
| 211 | Connecticut | Greenwich | 179600 | 42,800,000,000 | 238,307 |
| 212 | Florida | Lakeland | 255000 | 60,200,000,000 | 236,078 |
| 213 | New York | Corning | 56300 | 13,100,000,000 | 232,682 |
| 214 | Nevada | Reno | 50000 | 11,300,000,000 | 226,000 |
| 215 | New Jersey | Burlington | 47300 | 10,600,000,000 | 224,101 |
| 216 | Tennessee | Memphis | 559900 | 124,800,000,000 | 222,897 |
| 217 | New York | Armonk | 284500 | 62,800,000,000 | 220,738 |
| 218 | Virginia | Chesapeake | 139600 | 30,800,000,000 | 220,630 |
| 219 | Tennessee | Goodlettsville | 194200 | 40,600,000,000 | 209,063 |
| 220 | Illinois | Rolling Meadows | 56000 | 11,600,000,000 | 207,143 |
| 221 | California | Newport Beach | 134800 | 27,100,000,000 | 201,039 |
| 222 | North Carolina | Burlington | 65400 | 13,000,000,000 | 198,777 |
| 223 | Connecticut | Farmington | 72000 | 14,300,000,000 | 198,611 |
| 224 | California | Dublin | 107000 | 21,100,000,000 | 197,196 |
| 225 | New Jersey | Secaucus | 50500 | 9,900,000,000 | 196,040 |
| 226 | Missouri | Springfield | 85600 | 16,700,000,000 | 195,093 |
| 227 | Pennsylvania | King of Prussia | 87500 | 15,800,000,000 | 180,571 |
| 228 | North Carolina | Durham | 88000 | 15,400,000,000 | 175,000 |
| 229 | Massachusetts | Framingham | 364000 | 56,400,000,000 | 154,945 |
| 230 | Michigan | Southfield | 173700 | 23,300,000,000 | 134,139 |
| 231 | Connecticut | Wallingford | 125000 | 15,200,000,000 | 121,600 |
| 232 | Virginia | Ashburn | 130000 | 13,700,000,000 | 105,385 |
| 233 | Florida | Orlando | 191100 | 11,400,000,000 | 59,655 |
| 234 | New Jersey | Teaneck | 336800 | 19,700,000,000 | 58,492 |
| 235 | Texas | Plano | 245500 | 11,300,000,000 | 46,029 |
| 236 | California | Newark | 450000 | 9,600,000,000 | 21,333 |
In [147]:
dfusmaxeffct10 = dfusmaxeffct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])
gdfstsusmaxeffct10 = gdfsts.merge(dfusmaxeffct10, how = 'inner', on = ['State'])
gdfusactusmaxeffct10 = gdfusact.merge(dfusmaxeffct10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffct10
Out[147]:
| Zip Code | Latitude | Longitude | Population | geometry | State | City | Employees | Revenue (rounded) | Efficiency | Company | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | California | El Segundo | 500 | 9,700,000,000 | 19,400,000 | A-Mark Precious Metals |
| 1 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Ohio | Findlay | 18300 | 140,400,000,000 | 7,672,131 | Marathon Petroleum |
| 2 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Oklahoma | Oklahoma City | 2300 | 15,900,000,000 | 6,913,043 | Devon Energy |
| 3 | 19428 | 40 | -75 | 20,225 | POINT (-75.30317 40.08011) | Pennsylvania | Conshohocken | 44000 | 294,000,000,000 | 6,681,818 | Cencora |
| 4 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Texas | Midland | 2000 | 11,100,000,000 | 5,550,000 | Diamondback Energy |
| 5 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | Missouri | Chesterfield | 4100 | 22,100,000,000 | 5,390,244 | Reinsurance of America |
| 6 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Ohio | Dublin | 48400 | 226,800,000,000 | 4,685,950 | Cardinal Health |
| 7 | 55077 | 45 | -93 | 14,585 | POINT (-93.07574 44.81989) | Minnesota | Inver Grove Heights | 10700 | 39,300,000,000 | 3,672,897 | CHS |
| 8 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Texas | San Antonio | 47900 | 172,600,000,000 | 3,603,340 | Valero Energy |
| 9 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | Texas | San Antonio | 47900 | 172,600,000,000 | 3,603,340 | USAA |
| 10 | 06002 | 42 | -73 | 21,547 | POINT (-72.73714 41.84286) | Connecticut | Bloomfield | 72400 | 247,100,000,000 | 3,412,983 | Cigna |
In [148]:
musmaxeffct10 = gdfstsusmaxeffct10.explore(column='Efficiency', name='The Most Efficient City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffct10.explore(m=musmaxeffct10, column='Efficiency', name='The Most Efficient City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffct10)
musmaxeffct10
Out[148]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
In [149]:
# The Most Efficient State in US
dfusmaxeffst = df.groupby(['State'], as_index=False).sum('Employees')
dfusmaxeffst.insert(3,'Efficiency',1)
dfusmaxeffst['Efficiency'] = dfusmaxeffst['Revenue (rounded)'] / dfusmaxeffst['Employees']
dfusmaxeffst = dfusmaxeffst.sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfusmaxeffst10 = dfusmaxeffst.head(10)
dfusmaxeffst
Out[149]:
| State | Employees | Revenue (rounded) | Efficiency | |
|---|---|---|---|---|
| 0 | Oklahoma | 13300 | 48,100,000,000 | 3,616,541 |
| 1 | District of Columbia | 93200 | 185,200,000,000 | 1,987,124 |
| 2 | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 |
| 3 | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 |
| 4 | Kentucky | 134400 | 136,600,000,000 | 1,016,369 |
| 5 | Indiana | 336600 | 320,500,000,000 | 952,169 |
| 6 | Nebraska | 463100 | 427,000,000,000 | 922,047 |
| 7 | Missouri | 305400 | 262,600,000,000 | 859,856 |
| 8 | California | 2857700 | 2,399,300,000,000 | 839,591 |
| 9 | Ohio | 1255100 | 1,035,800,000,000 | 825,273 |
| 10 | Oregon | 109600 | 88,000,000,000 | 802,920 |
| 11 | New York | 2825500 | 2,085,200,000,000 | 737,993 |
| 12 | Wisconsin | 196500 | 144,900,000,000 | 737,405 |
| 13 | Pennsylvania | 929200 | 672,400,000,000 | 723,633 |
| 14 | Michigan | 838000 | 602,400,000,000 | 718,854 |
| 15 | Louisiana | 37300 | 25,000,000,000 | 670,241 |
| 16 | Connecticut | 806700 | 532,100,000,000 | 659,601 |
| 17 | Kansas | 14000 | 9,100,000,000 | 650,000 |
| 18 | Arizona | 194000 | 125,000,000,000 | 644,330 |
| 19 | Minnesota | 1269900 | 802,600,000,000 | 632,018 |
| 20 | Illinois | 1655400 | 1,040,200,000,000 | 628,368 |
| 21 | Colorado | 194000 | 117,000,000,000 | 603,093 |
| 22 | Iowa | 52800 | 31,000,000,000 | 587,121 |
| 23 | North Carolina | 856900 | 469,300,000,000 | 547,672 |
| 24 | Alabama | 31600 | 16,800,000,000 | 531,646 |
| 25 | Delaware | 24000 | 12,400,000,000 | 516,667 |
| 26 | Virginia | 1461200 | 738,400,000,000 | 505,338 |
| 27 | Washington | 2750600 | 1,299,400,000,000 | 472,406 |
| 28 | New Jersey | 944300 | 440,900,000,000 | 466,907 |
| 29 | Massachusetts | 854000 | 384,500,000,000 | 450,234 |
| 30 | Idaho | 244600 | 104,300,000,000 | 426,410 |
| 31 | Florida | 1058700 | 448,700,000,000 | 423,822 |
| 32 | Georgia | 1327300 | 548,300,000,000 | 413,094 |
| 33 | Maryland | 290200 | 119,700,000,000 | 412,474 |
| 34 | Arkansas | 2283200 | 764,300,000,000 | 334,749 |
| 35 | Tennessee | 1190500 | 312,700,000,000 | 262,663 |
| 36 | Nevada | 159100 | 39,800,000,000 | 250,157 |
In [150]:
dfusmaxeffst10 = dfusmaxeffst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])
gdfstsusmaxeffst10 = gdfsts.merge(dfusmaxeffst10, how = 'inner', on = ['State'])
gdfusactusmaxeffst10 = gdfusact.merge(dfusmaxeffst10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffst10
Out[150]:
| Zip Code | Latitude | Longitude | Population | geometry | State | Employees | Revenue (rounded) | Efficiency | City | Company | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 74172 | 36 | -96 | 0 | POINT (-95.9905 36.1544) | Oklahoma | 13300 | 48,100,000,000 | 3,616,541 | Tulsa | Williams |
| 1 | 73102 | 35 | -98 | 3,590 | POINT (-97.5191 35.47065) | Oklahoma | 13300 | 48,100,000,000 | 3,616,541 | Oklahoma City | Devon Energy |
| 2 | 74103 | 36 | -96 | 2,419 | POINT (-95.9957 36.15617) | Oklahoma | 13300 | 48,100,000,000 | 3,616,541 | Tulsa | Oneok |
| 3 | 20037 | 39 | -77 | 12,441 | POINT (-77.0535 38.89213) | District of Columbia | 93200 | 185,200,000,000 | 1,987,124 | Washington | Danaher |
| 4 | 20003 | 39 | -77 | 36,194 | POINT (-76.99033 38.88193) | District of Columbia | 93200 | 185,200,000,000 | 1,987,124 | Washington | Xylem |
| 5 | 20005 | 39 | -77 | 12,960 | POINT (-77.0316 38.90443) | District of Columbia | 93200 | 185,200,000,000 | 1,987,124 | Washington | Fannie Mae |
| 6 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 | Providence | Textron |
| 7 | 02895 | 42 | -71 | 43,081 | POINT (-71.49923 42.00103) | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 | Woonsocket | CVS Health |
| 8 | 02919 | 42 | -72 | 29,473 | POINT (-71.52002 41.82733) | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 | Johnston | FM |
| 9 | 02908 | 42 | -71 | 39,661 | POINT (-71.43926 41.83877) | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 | Providence | United Natural Foods |
| 10 | 02903 | 42 | -71 | 12,309 | POINT (-71.41003 41.81902) | Rhode Island | 344900 | 440,300,000,000 | 1,276,602 | Providence | Citizens Financial |
| 11 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Targa Resources |
| 12 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Waste Management |
| 13 | 76011 | 33 | -97 | 22,297 | POINT (-97.08223 32.7543) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Arlington | D.R. Horton |
| 14 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | EOG Resources |
| 15 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | NRG Energy |
| 16 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Plains GP |
| 17 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Enterprise Products Partners |
| 18 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Chevron |
| 19 | 76262 | 33 | -97 | 43,589 | POINT (-97.22101 33.01137) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Westlake | Charles Schwab |
| 20 | 76155 | 33 | -97 | 6,301 | POINT (-97.04911 32.82404) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Fort Worth | American Airlines |
| 21 | 75225 | 33 | -97 | 22,383 | POINT (-96.79109 32.86511) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | Energy Transfer |
| 22 | 75254 | 33 | -97 | 24,737 | POINT (-96.80127 32.94571) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | Tenet Healthcare |
| 23 | 75243 | 33 | -97 | 63,907 | POINT (-96.73633 32.91232) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | Texas Instruments |
| 24 | 75240 | 33 | -97 | 24,718 | POINT (-96.78924 32.93194) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | AECOM |
| 25 | 75235 | 33 | -97 | 19,067 | POINT (-96.84798 32.83219) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | Southwest Airlines |
| 26 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Kinder Morgan |
| 27 | 75219 | 33 | -97 | 25,001 | POINT (-96.81315 32.81087) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | HF Sinclair |
| 28 | 75202 | 33 | -97 | 2,744 | POINT (-96.8037 32.77843) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | AT&T |
| 29 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | Jacobs Solutions |
| 30 | 75201 | 33 | -97 | 18,078 | POINT (-96.79953 32.78826) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Dallas | CBRE |
| 31 | 75074 | 33 | -97 | 53,146 | POINT (-96.67304 33.03298) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Plano | Yum China s |
| 32 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Cheniere Energy |
| 33 | 77019 | 30 | -95 | 23,662 | POINT (-95.41212 29.75318) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Corebridge Financial |
| 34 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | CenterPoint Energy |
| 35 | 77002 | 30 | -95 | 19,616 | POINT (-95.36538 29.75635) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | KBR |
| 36 | 78682 | 30 | -98 | 0 | POINT (-97.7273 30.4076) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Round Rock | Dell Technologies |
| 37 | 78288 | 29 | -98 | 0 | POINT (-98.4935 29.4239) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | San Antonio | USAA |
| 38 | 79701 | 32 | -102 | 27,678 | POINT (-102.08105 31.99239) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Midland | Diamondback Energy |
| 39 | 78741 | 30 | -98 | 45,274 | POINT (-97.71389 30.23007) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Austin | Oracle |
| 40 | 78725 | 30 | -98 | 10,810 | POINT (-97.60859 30.23554) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Austin | Tesla |
| 41 | 78249 | 30 | -99 | 61,772 | POINT (-98.614 29.56752) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | San Antonio | Valero Energy |
| 42 | 78130 | 30 | -98 | 95,787 | POINT (-98.06877 29.69224) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | New Braunfels | Rush Enterprises |
| 43 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Spring | Hewlett Packard |
| 44 | 77389 | 30 | -96 | 44,545 | POINT (-95.50752 30.11509) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Spring | Exxon Mobil |
| 45 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Baker Hughes |
| 46 | 77079 | 30 | -96 | 35,540 | POINT (-95.6037 29.77632) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | ConocoPhillips |
| 47 | 77077 | 30 | -96 | 63,421 | POINT (-95.64189 29.75375) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Sysco |
| 48 | 77056 | 30 | -95 | 23,314 | POINT (-95.46806 29.74849) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Westlake |
| 49 | 77046 | 30 | -95 | 1,873 | POINT (-95.43301 29.73438) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Occidental Petroleum |
| 50 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | NOV |
| 51 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | APA |
| 52 | 77042 | 30 | -96 | 40,725 | POINT (-95.56015 29.74125) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Phillips 66 |
| 53 | 77032 | 30 | -95 | 13,536 | POINT (-95.34004 29.96523) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Halliburton |
| 54 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Par Pacific |
| 55 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Celanese |
| 56 | 77008 | 30 | -95 | 40,155 | POINT (-95.41766 29.79856) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | Quanta Services |
| 57 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Commercial Metals |
| 58 | 77024 | 30 | -96 | 37,647 | POINT (-95.50869 29.77073) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Houston | 1 Automotive |
| 59 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Fluor |
| 60 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Vistra |
| 61 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Caterpillar |
| 62 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | McKesson |
| 63 | 75038 | 33 | -97 | 33,097 | POINT (-96.97946 32.87231) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Kimberly-Clark |
| 64 | 75039 | 33 | -97 | 22,450 | POINT (-96.94042 32.88592) | Texas | 2432800 | 2,680,800,000,000 | 1,101,940 | Irving | Builders FirstSource |
| 65 | 40213 | 38 | -86 | 15,805 | POINT (-85.71571 38.177) | Kentucky | 134400 | 136,600,000,000 | 1,016,369 | Louisville | Yum Brands |
| 66 | 40222 | 38 | -86 | 21,634 | POINT (-85.61173 38.26436) | Kentucky | 134400 | 136,600,000,000 | 1,016,369 | Louisville | BrightSpring Health Services |
| 67 | 40202 | 38 | -86 | 7,109 | POINT (-85.75205 38.25288) | Kentucky | 134400 | 136,600,000,000 | 1,016,369 | Louisville | Humana |
| 68 | 46285 | 40 | -86 | 0 | POINT (-86.1582 39.7683) | Indiana | 336600 | 320,500,000,000 | 952,169 | Indianapolis | Eli Lilly |
| 69 | 47710 | 38 | -88 | 18,802 | POINT (-87.57618 38.02518) | Indiana | 336600 | 320,500,000,000 | 952,169 | Evansville | Berry Global |
| 70 | 47201 | 39 | -86 | 48,602 | POINT (-85.99432 39.15074) | Indiana | 336600 | 320,500,000,000 | 952,169 | Columbus | Cummins |
| 71 | 46804 | 41 | -85 | 29,177 | POINT (-85.23913 41.05421) | Indiana | 336600 | 320,500,000,000 | 952,169 | Fort Wayne | Steel Dynamics |
| 72 | 46580 | 41 | -86 | 21,812 | POINT (-85.87212 41.20884) | Indiana | 336600 | 320,500,000,000 | 952,169 | Warsaw | Zimmer Biomet s |
| 73 | 46514 | 42 | -86 | 41,480 | POINT (-85.97547 41.72328) | Indiana | 336600 | 320,500,000,000 | 952,169 | Elkhart | THOR Industries |
| 74 | 46268 | 40 | -86 | 25,623 | POINT (-86.23253 39.89769) | Indiana | 336600 | 320,500,000,000 | 952,169 | Indianapolis | Corteva |
| 75 | 46204 | 40 | -86 | 11,022 | POINT (-86.15703 39.77134) | Indiana | 336600 | 320,500,000,000 | 952,169 | Indianapolis | Elevance Health |
| 76 | 68175 | 41 | -96 | 0 | POINT (-95.96584 41.26502) | Nebraska | 463100 | 427,000,000,000 | 922,047 | Omaha | Mutual of Omaha Insurance |
| 77 | 68131 | 41 | -96 | 13,928 | POINT (-95.96479 41.26435) | Nebraska | 463100 | 427,000,000,000 | 922,047 | Omaha | Berkshire Hathaway |
| 78 | 68179 | 41 | -96 | 0 | POINT (-95.9352 41.2597) | Nebraska | 463100 | 427,000,000,000 | 922,047 | Omaha | Union Pacific |
| 79 | 68102 | 41 | -96 | 9,311 | POINT (-95.93224 41.26231) | Nebraska | 463100 | 427,000,000,000 | 922,047 | Omaha | Peter Kiewit Sons' |
| 80 | 65802 | 37 | -93 | 46,005 | POINT (-93.35167 37.21048) | Missouri | 305400 | 262,600,000,000 | 859,856 | Springfield | O'Reilly Automotive |
| 81 | 63144 | 39 | -90 | 9,580 | POINT (-90.3482 38.61943) | Missouri | 305400 | 262,600,000,000 | 859,856 | St. Louis | Post s |
| 82 | 63146 | 39 | -90 | 30,917 | POINT (-90.47634 38.70135) | Missouri | 305400 | 262,600,000,000 | 859,856 | St. Louis | Core & Main |
| 83 | 63105 | 39 | -90 | 18,860 | POINT (-90.32812 38.64427) | Missouri | 305400 | 262,600,000,000 | 859,856 | St. Louis | Centene |
| 84 | 63105 | 39 | -90 | 18,860 | POINT (-90.32812 38.64427) | Missouri | 305400 | 262,600,000,000 | 859,856 | St. Louis | Graybar Electric |
| 85 | 63131 | 39 | -90 | 17,993 | POINT (-90.44365 38.6172) | Missouri | 305400 | 262,600,000,000 | 859,856 | Des Peres | Edward Jones |
| 86 | 63017 | 39 | -91 | 43,074 | POINT (-90.53722 38.65143) | Missouri | 305400 | 262,600,000,000 | 859,856 | Chesterfield | Reinsurance of America |
| 87 | 63136 | 39 | -90 | 41,314 | POINT (-90.25979 38.74418) | Missouri | 305400 | 262,600,000,000 | 859,856 | St. Louis | Emerson Electric |
| 88 | 94588 | 38 | -122 | 34,423 | POINT (-121.88178 37.73801) | California | 2857700 | 2,399,300,000,000 | 839,591 | Pleasanton | Workday |
| 89 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | 839,591 | Palo Alto | HP |
| 90 | 94560 | 38 | -122 | 47,145 | POINT (-122.02523 37.50771) | California | 2857700 | 2,399,300,000,000 | 839,591 | Newark | Concentrix |
| 91 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | 839,591 | Fremont | Lam Research |
| 92 | 94538 | 38 | -122 | 67,704 | POINT (-121.96361 37.50653) | California | 2857700 | 2,399,300,000,000 | 839,591 | Fremont | TD Synnex |
| 93 | 94404 | 38 | -122 | 35,950 | POINT (-122.26905 37.5562) | California | 2857700 | 2,399,300,000,000 | 839,591 | Foster City | Gilead Sciences |
| 94 | 94403 | 38 | -122 | 43,459 | POINT (-122.30454 37.53844) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Mateo | Franklin Resources |
| 95 | 94304 | 37 | -122 | 4,731 | POINT (-122.16699 37.39744) | California | 2857700 | 2,399,300,000,000 | 839,591 | Palo Alto | Broadcom |
| 96 | 94111 | 38 | -122 | 4,553 | POINT (-122.3998 37.79847) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Prologis |
| 97 | 94158 | 38 | -122 | 11,206 | POINT (-122.39153 37.77116) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Uber |
| 98 | 94109 | 38 | -122 | 54,397 | POINT (-122.42138 37.79334) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Williams-Sonoma |
| 99 | 94107 | 38 | -122 | 30,190 | POINT (-122.39508 37.76473) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | DoorDash |
| 100 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Gap |
| 101 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Visa |
| 102 | 94105 | 38 | -122 | 14,890 | POINT (-122.39707 37.79239) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Salesforce |
| 103 | 94104 | 38 | -122 | 478 | POINT (-122.40211 37.79144) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Wells Fargo |
| 104 | 94568 | 38 | -122 | 70,542 | POINT (-121.90113 37.71596) | California | 2857700 | 2,399,300,000,000 | 839,591 | Dublin | Ross Stores |
| 105 | 95125 | 37 | -122 | 53,934 | POINT (-121.89408 37.29554) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Ebay |
| 106 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | 839,591 | Oakland | PG&E |
| 107 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | Palo Alto Networks |
| 108 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Sanmina |
| 109 | 95134 | 37 | -122 | 30,255 | POINT (-121.94528 37.43003) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Cisco Systems |
| 110 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Super Micro Computer |
| 111 | 95131 | 37 | -122 | 30,745 | POINT (-121.89793 37.38729) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | PayPal |
| 112 | 94086 | 37 | -122 | 48,956 | POINT (-122.02316 37.37164) | California | 2857700 | 2,399,300,000,000 | 839,591 | Sunnyvale | Intuitive Surgical |
| 113 | 95119 | 37 | -122 | 10,449 | POINT (-121.79077 37.22756) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Western Digital |
| 114 | 95110 | 37 | -122 | 19,444 | POINT (-121.9097 37.34656) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Jose | Adobe |
| 115 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | ServiceNow |
| 116 | 94612 | 38 | -122 | 17,663 | POINT (-122.2662 37.80789) | California | 2857700 | 2,399,300,000,000 | 839,591 | Oakland | Block |
| 117 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | Advanced Micro Devices |
| 118 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | Applied Materials |
| 119 | 95054 | 37 | -122 | 25,196 | POINT (-121.96483 37.39308) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | Intel |
| 120 | 95051 | 37 | -122 | 61,345 | POINT (-121.98444 37.3483) | California | 2857700 | 2,399,300,000,000 | 839,591 | Santa Clara | Nvidia |
| 121 | 95035 | 37 | -122 | 78,479 | POINT (-121.87632 37.44319) | California | 2857700 | 2,399,300,000,000 | 839,591 | Milpitas | KLA |
| 122 | 95032 | 37 | -122 | 27,682 | POINT (-121.92359 37.20859) | California | 2857700 | 2,399,300,000,000 | 839,591 | Los Gatos | Netflix |
| 123 | 95014 | 37 | -122 | 61,109 | POINT (-122.07981 37.30827) | California | 2857700 | 2,399,300,000,000 | 839,591 | Cupertino | Apple |
| 124 | 94103 | 38 | -122 | 33,524 | POINT (-122.41136 37.77299) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Francisco | Airbnb |
| 125 | 92612 | 34 | -118 | 33,706 | POINT (-117.82457 33.65984) | California | 2857700 | 2,399,300,000,000 | 839,591 | Irvine | Ingram Micro |
| 126 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | 839,591 | Redwood City | Electronic Arts |
| 127 | 91770 | 34 | -118 | 58,893 | POINT (-118.08361 34.06395) | California | 2857700 | 2,399,300,000,000 | 839,591 | Rosemead | Edison International |
| 128 | 94065 | 38 | -122 | 11,620 | POINT (-122.24683 37.53504) | California | 2857700 | 2,399,300,000,000 | 839,591 | Redwood City | Equinix |
| 129 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | 839,591 | Beverly Hills | Live Nation Entertainment |
| 130 | 90210 | 34 | -118 | 19,652 | POINT (-118.41505 34.10251) | California | 2857700 | 2,399,300,000,000 | 839,591 | Beverly Hills | Endeavor |
| 131 | 90245 | 34 | -118 | 16,863 | POINT (-118.40161 33.91709) | California | 2857700 | 2,399,300,000,000 | 839,591 | El Segundo | A-Mark Precious Metals |
| 132 | 90266 | 34 | -118 | 34,584 | POINT (-118.39705 33.88968) | California | 2857700 | 2,399,300,000,000 | 839,591 | Manhattan Beach | Skechers U.S.A. |
| 133 | 90802 | 34 | -118 | 39,859 | POINT (-118.21143 33.75035) | California | 2857700 | 2,399,300,000,000 | 839,591 | Long Beach | Molina Healthcare |
| 134 | 91320 | 34 | -119 | 43,628 | POINT (-118.94795 34.17339) | California | 2857700 | 2,399,300,000,000 | 839,591 | Thousand Oaks | Amgen |
| 135 | 91367 | 34 | -119 | 45,427 | POINT (-118.61518 34.17708) | California | 2857700 | 2,399,300,000,000 | 839,591 | Woodland Hills | Farmers Insurance Exchange |
| 136 | 91521 | 34 | -118 | 11,049 | POINT (-118.3252 34.1569) | California | 2857700 | 2,399,300,000,000 | 839,591 | Burbank | Walt Disney |
| 137 | 92101 | 33 | -117 | 48,163 | POINT (-117.18589 32.7162) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Diego | Sempra |
| 138 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Diego | LPL Financial s |
| 139 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | 839,591 | Newport Beach | Pacific Life |
| 140 | 92660 | 34 | -118 | 34,788 | POINT (-117.87504 33.63375) | California | 2857700 | 2,399,300,000,000 | 839,591 | Newport Beach | Chipotle Mexican Grill |
| 141 | 92879 | 34 | -118 | 48,756 | POINT (-117.5357 33.87979) | California | 2857700 | 2,399,300,000,000 | 839,591 | Corona | Monster Beverage |
| 142 | 94025 | 37 | -122 | 40,230 | POINT (-122.1829 37.45087) | California | 2857700 | 2,399,300,000,000 | 839,591 | Menlo Park | Meta |
| 143 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | 839,591 | Mountain View | Alphabet |
| 144 | 92121 | 33 | -117 | 4,157 | POINT (-117.20231 32.8973) | California | 2857700 | 2,399,300,000,000 | 839,591 | San Diego | Qualcomm |
| 145 | 94043 | 37 | -122 | 32,042 | POINT (-122.06892 37.41188) | California | 2857700 | 2,399,300,000,000 | 839,591 | Mountain View | Intuit |
| 146 | 45263 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | Fifth Third Bancorp |
| 147 | 43287 | 40 | -83 | 905,748 | POINT (-83.0011 39.9619) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Columbus | Huntington Bancshares |
| 148 | 43659 | 42 | -84 | 0 | POINT (-83.5554 41.6639) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Toledo | Owens Corning |
| 149 | 44316 | 41 | -81 | 0 | POINT (-81.47083 41.07854) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Akron | Goodyear Tire & Rubber |
| 150 | 45262 | 39 | -84 | 0 | POINT (-84.4569 39.1616) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | Cintas |
| 151 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | Western & Southern Financial |
| 152 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | Kroger |
| 153 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | Procter & Gamble |
| 154 | 44667 | 41 | -82 | 13,688 | POINT (-81.76495 40.83386) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Orrville | J.M. Smucker |
| 155 | 45202 | 39 | -85 | 17,022 | POINT (-84.50243 39.10885) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cincinnati | American Financial |
| 156 | 45215 | 39 | -84 | 30,806 | POINT (-84.46221 39.23536) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Evendale | General Electric |
| 157 | 45840 | 41 | -84 | 54,342 | POINT (-83.64943 41.02626) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Findlay | Marathon Petroleum |
| 158 | 45014 | 39 | -85 | 45,652 | POINT (-84.5521 39.32822) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Fairfield | Cincinnati Financial |
| 159 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cleveland | Sherwin-Williams |
| 160 | 44308 | 41 | -82 | 1,261 | POINT (-81.51751 41.0818) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Akron | FirstEnergy |
| 161 | 44143 | 42 | -81 | 24,337 | POINT (-81.47513 41.55358) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Mayfield Village | Progressive |
| 162 | 44124 | 41 | -81 | 40,046 | POINT (-81.46774 41.49999) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cleveland | Parker-Hannifin |
| 163 | 44115 | 41 | -82 | 10,389 | POINT (-81.66999 41.49211) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cleveland | TransDigm |
| 164 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cleveland | KeyCorp |
| 165 | 44114 | 42 | -82 | 7,472 | POINT (-81.67625 41.5137) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Cleveland | Cleveland-Cliffs |
| 166 | 44060 | 42 | -81 | 60,257 | POINT (-81.32806 41.67742) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Mentor | Avery Dennison |
| 167 | 43615 | 42 | -84 | 40,813 | POINT (-83.67255 41.65045) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Toledo | Welltower |
| 168 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Maumee | Andersons |
| 169 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Columbus | American Electric Power |
| 170 | 43215 | 40 | -83 | 16,999 | POINT (-83.01262 39.96633) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Columbus | Nationwide |
| 171 | 43082 | 40 | -83 | 33,799 | POINT (-82.88437 40.15537) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Westerville | Vertiv s |
| 172 | 43017 | 40 | -83 | 41,422 | POINT (-83.13314 40.1189) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Dublin | Cardinal Health |
| 173 | 43537 | 42 | -84 | 29,639 | POINT (-83.68542 41.57433) | Ohio | 1255100 | 1,035,800,000,000 | 825,273 | Maumee | Dana |
In [151]:
musmaxeffst10 = gdfstsusmaxeffst10.explore(column='Efficiency', name='The Most Efficient State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffst10.explore(m=musmaxeffst10, column='Efficiency', name='The Most Efficient State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffst10)
musmaxeffst10
Out[151]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
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